Detection of environmental pollution

Abstract

The present invention provides a method of detecting an unrecognised environmental polluting event, comprising: (i) measuring the level of one or more bioindicators in a sample obtained from individuals in a first geospatially defined population; and (ii) comparing the level of the one or more bioindicators in the first geospatially defined population to the level of the same one or more bioindicators in a distinct geospatially defined population, or a control value; wherein a statistically significant difference in the level of the one or more bioindicators between the first geospatially defined population and the distinct geospatially defined population, or the control value, is indicative that the first geospatially defined population has been exposed to an environmental polluting event.

Description

[0001] DETECTION OF ENVIRONMENTAL POLLUTION

[0002] FIELD OF THE INVENTION

[0003] The invention relates to a method alerting to the occurrence of an unrecognised environmental polluting event, and biomarkers for use therein.

[0004] BACKGROUND

[0005] Environmental pollution, whether chronic or acute, impacts ecosystems and is damaging to health and methods of its monitoring are desirable. It is estimated that nearly a quarter of the global disease burden is attributable to environmental factors, including biological and chemical factors (Hanging 2022).

[0006] Acute polluting events are isolated high impact occurrences such as the radiation release at Chernobyl and the dioxin release in Seveso, Italy whereas a chronic polluting event is one which occurs repeatedly or continuously, often unnoticed, and includes vehicular gaseous and particulate emission and the release of effluent, wastewater recycling and the run-off of agricultural chemicals into water bodies. Small molecules and elements of less than 1000 Daltons are often involved in chronic polluting events and can be referred to as environmental toxicants (ETs). Chronic polluting events are usually tolerated and managed within legal frameworks that often incorporate an allowable concentration threshold of the polluting species. The health impact of an acute polluting event is usually more immediate, though both acute and chronic events can be detrimental to health over periods of months and years.

[0007] Vehicle pollution arising from combustion products, tyre and brake particulates are well-established as being detrimental to health, and constant exposure to areas of high traffic density is known to impact lung health, promote hypertension and exacerbate conditions such as asthma.

[0008] Water bodies, especially open water, are particularly susceptible to polluting events which can be detrimental to health at the point of pollution and in downstream sources such as domestic water. Chemical pollutants in water bodies are derived from fertilizer and pesticide run-off from agricultural land, sewage and indirect and direct dumping of industrial waste. Furthermore, domestic wastewater discharge introduces pharmaceutical, hygiene and cleaning chemicals and food-based chemicals into the water system. Many chemicals polluting water bodies are known to be detrimental to short-term and long-term animal and human health and include endocrine disruptors which have proximate impact on fertility and cancer-causing chemicals. A main source of endocrine disruptors in tap / domestic drinking water originates from domestic wastewater discharge. Domestic wastewater contaminants can re-enter the water supply chain as the treatment processes to remove low molecular weight species is not fully effective and chronic exposure can occur. Recent chemicals of concern are the unregulated polyfluoroalkyls substances (PFAS), also known as ‘forever chemicals’ due to their stability and high biological half-life. Their ubiquitous presence in drinking water is concerning and knowledge of their detrimental health effects is incomplete though they are known to impact the endocrine system and impact reproduction (Rickard 2022). Agriculture-based contaminants such as phosphate and nitrate-based fertilizers promote eutrophication which is exacerbated by higher temperatures and the frequency, duration and severity of so-called algal blooms, especially in lakes and reservoirs, is increasing globally, having wide-ranging economic impacts on aquaculture, tourism and recreation. Of particular concern is the potential impact to public health; environmental toxins produced by the cyanobacteria of algal blooms are known to produce dermal, gastrointestinal and neurotoxic effects (Lim 2023).

[0009] Although water treatment prior to domestic supply prevents damage to health by acute pollution events and mitigates the impact of chronic polluting events, the amount and diverse nature of the polluting molecules means that they still occur in domestic water (https: / / www.epa.gov / ground-water-and-drinking- water / summary-cyanotoxins-treatment-drinking-water 31 / 05 / 2024), and often remain completely unknown. The long-term effect to health of prolonged exposure to ETs in domestic water and the potential additive or synergistic concentration impact of two or more polluting chemicals is not known. Certain biomarkers can be used to monitor recognised environmental polluting events (EPE). However, as environmental polluting events, particularly chronic pollution, are generally slow acting, adverse effects to ecosystems and the health of individuals may go unnoticed for several months or years. In addition, due to the number and diversity of ETs and their possible means for contamination, environmental polluting events remain unrecognised. Proactive methods of alerting to the occurrence of an unrecognised EPEs are therefore desirable.

[0010] SUMMARY OF INVENTION

[0011] Unrecognised pollution, especially chronic pollution, is widespread and increasing in incidence and its expedient and practical detection is desirable. The present application provides novel, proactive methods which utilise health measurement data of individuals in geospatially defined populations to identify differences in such measurements between populations and thus a potential environmental polluting event (EPE). The identification of an environmental polluting event using biomarkers enables affected individuals to respond to the impact of the toxicants, which is especially important for the affected individuals if the environmental polluting event is continuous or continual. If an environmental polluting event is suspected or identified, action can be taken to prevent, reverse or mitigate the event, with or without additional investigation of the potential environmental polluting event, and thus safeguard the wellbeing of the affected individuals, population and local environment.

[0012] In performing such analysis in the described method, the inventors of the present invention have further surprisingly identified changes to certain biomarkers triggered by specific types of environmental polluting events, namely (domestic tap) water pollution, radon exposure and air pollution exposure. This allows the monitoring of health and wellbeing in relation to exposure to environmental toxicants at the level of the individual.

[0013] Accordingly, in a first aspect, the invention provides a method of detecting an unrecognised environmental polluting event, comprising: (i) measuring the level of one or more bioindicators in a sample obtained from individuals in a first geospatially defined population; and (ii) comparing the level of the one or more bioindicators in the first geospatially defined population to the level of the same one or more bioindicators in a distinct geospatially defined population, or a control value; wherein a statistically significant difference in the level of the one or more bioindicators between the first geospatially defined population and the distinct geospatially defined population, or the control value, is indicative that the first geospatially defined population has been exposed to an environmental polluting event.

[0014] In some embodiments, the method of the first aspect may be used to determine an appropriate course of action for the population that has been exposed to an environmental polluting event.

[0015] In a second aspect, the invention provides a method of identifying whether an individual has been exposed to air pollution, comprising measuring the amount of one or more of Magnesium and Parathyroid hormone in an ex vivo sample obtained from the individual at time Ti ; and measuring the amount of one or more of Magnesium and Parathyroid hormone in an ex vivo sample obtained from the individual at a time T2, wherein a decrease in the amount of Magnesium and / or Parathyroid hormone between T1 and T2 indicates that the individual has been exposed to air pollution.

[0016] In some embodiments, the method of the second aspect may be used to determine an appropriate course of action for the affected individual.

[0017] In a third aspect, the invention provides a method of identifying whether a female individual has been exposed to polluted water, comprising measuring the amount of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid in an ex vivo sample obtained from the individual at a time T1; and measuring the amount of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid in an ex vivo sample obtained from the individual at a time T2, wherein a decrease in the amount of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid indicates between T1 and T2 that the individual has been exposed to polluted water. In some embodiments, the method of the third aspect may be used to determine an appropriate course of action for the affected female individual.

[0018] In a fourth aspect there is provided a computer-implemented method for detecting an unrecognised environmental polluting event, (EPE) the method comprising: receiving, by an input module, first bioindicator measurement data for a first group of individuals in a first geospatially defined population, wherein the first bioindicator measurement data comprises a first level of one or more bioindicators in a sample obtained from the first group of individuals; obtaining, by the input module, comparison data comprising a second level of the same one or more bioindicators; comparing, by a processor, the first bioindicator measurement data of the first group of individuals with the comparison data; determining, by the processor, whether there is a statistically significant difference between the first level of one or more bioindicators and the second level of the one or more bioindicators; and if it is determined there is a statistically significant difference: outputting, by an output module, an indication that the first group of individuals in the first geospatially defined population has been exposed to an EPE.

[0019] In a fifth aspect there is provided a computer program product comprising instructions which, when executed by one or more processors, cause the processors to perform the computer-implemented method.

[0020] In a sixth aspect there is provided a system for detecting an unrecognised environmental polluting event, EPE, comprising: a data input module: receive first bioindicator measurement data for a first group of individuals in a first geospatially defined population, wherein the first bioindicator measurement data comprises a first level of one or more bioindicators in a sample obtained from the first group of individuals; and obtain comparison data comprising a second level of the same one or more bioindicators; a processing module configured to: compare the first bioindicator measurement data of the first group of individuals with the comparison data; and determine whether there is a statistically significant difference between the first level of one or more bioindicators and the second level of the one or more bioindicators; an output module configured to: if it is determined there is a statistically significant difference, output an indication that the first group of individuals in the first geospatially defined population has been exposed to an EPE.

[0021] In a seventh aspect there is provided a computer-implemented method of determining whether an individual has been exposed to air pollution, the method comprising: obtaining a first value of one or more of Magnesium and Parathyroid hormone in an ex vivo sample obtained from the individual at time Ti; and obtaining a second value of one or more of Magnesium and Parathyroid hormone in an ex vivo sample obtained from the individual at a time T2; comparing the first value and the second value; and outputting an indication that the individual has been exposed to air pollution when the comparison indicates that the second value is less than the first value.

[0022] In an eighth aspect there is provided a computer-implemented method of determining whether a female individual has been exposed to polluted water, the method comprising: obtaining a first value of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid in an ex vivo sample obtained from the individual at a time T1; obtaining a second value of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid in an ex vivo sample obtained from the individual at a time T2; comparing the first value with the second value; and outputting an indication that the individual has been exposed to polluted water when the comparison indicates that the second value is less than the first value.

[0023] BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 : Schematic outlining the geospatial-biomarker method of EPE detection

[0025] Figure 2: Hypothetical graphical representation of the utility of the described geospatial method to support the identification of a possible polluting event.

[0026] Figure 3: Graph showing the utility of the described geospatial method to support the identification of a possible polluting event in locations in Northern Ireland whose domestic tap water is supplied from Lough Neagh (Belfast, Coleraine, Lisburn & Portadown) or Silent Valley (Bangor, Newtownards). This shows lower levels in females (mean & standard error of mean displayed) of the biochemicals FSH & LH in Coleraine, Belfast, Lisburn and Belfast compared to Bangor and Newtownards.

[0027] Figure 4: Map showing the locations of Figure 3 (Ards= Newtownards).

[0028] Figure 5: Graph of FSH, LH and FA concentrations in female populations whose domestic water supply is sourced from Lough Neagh or Silent Valley. Numbers on the graph between two columns for a specific age range are p-values derived from t-test / Mann-Whitney analysis.

[0029] Figure 6: Graph comparing female levels of FA, FSH and LH in three towns whose domestic tap water source is Lough Neagh.

[0030] Figure 7: Graphs displaying the ratios of diverse pollutants in domestic water derived from Lough Neagh (100%) and Silent Valley. Ratios correspond to domestic tap water supply and for each location corresponds to the mean of three water supply zones; trihalomethanes are trichloromethane, tribromomethane, dibromochloromethane and bromodichloromethane (Data was obtained from Nl Water website, Nl Water Customer Tap Public Registers and Drinking Water Quality Annual Reports).

[0031] Figure 8: Flow diagram outlining the geospatial-biomarker method of EPE detection.

[0032] DETAILED DESCRIPTION

[0033] The present application provides novel, proactive methods which utilise health measurement data of individuals in geospatially defined populations to identify differences in such measurements between populations and thus unrecognised environmental polluting events.

[0034] Environmental polluting events can damage both the environment and the health of individuals residing in or who are indirectly exposed to the toxic environment and can be categorised as chronic and acute. Chronic environmental pollution, unlike acute pollution, is usually associated with a gradual, unnoticed build-up of toxicants and toxic breakdown products. Environmental pollution and the regulations determining the allowable concentration of polluting species are managed by governmental regulatory agencies. However, the detrimental longterm effects of chronic pollution are generally ignored, tolerated or unknown. Furthermore, it is difficult to attribute and disentangle the impact of chronic pollution from other drivers of disease and ill-health such as pathogens, socioeconomic factors, diet and lack of exercise, especially in the absence of targeted studies and / or suitable methods for its detection. Biological organisms have been used or suggested for use in environmental health bioindication, but their practical application is limited. Although the impact of chronic pollution on human health and wellbeing is known, the use of human populations for active bioindication to provide an early warning of chronic environmental pollution is not known.

[0035] The current methods describe cost-effective and readily implemented human bioindication methods for identifying acute and chronic pollution events using existing technology, infrastructure and systems. Figure 1 shows an outline of the present method. Figure 2 shows a hypothetical use of the results of such a method.

[0036] The methods of the invention are exemplified using three environmental polluting events: domestic water source pollution, radon gas air pollution and particulate / NO2 air pollution.

[0037] As a proof-of-concept for the use of health measurement data as a bioindicator for identifying possible environmental polluting events, two populations, each receiving their drinking water supply from a different reservoir source in Northern Ireland (Lough Neagh and three reservoirs from Silent Valley in the Mourne Mountains), were tested by the present inventors.

[0038] Lough Neagh in Northern Ireland is the largest lake in the United Kingdom. Increasing agricultural run-off and domestic / industrial sewerage and waste combined with proliferating algal blooms has seriously impacted the health of the lake. The presence of pollutants within a waterbody (e.g., pesticides and other small molecules derived from sewage and agricultural run-off) is not always known prior to the noticeable occurrence of algal blooms. Lough Neagh is the source of 40% of domestic drinking water in Northern Ireland and an increase in pollution leads to an increase in risk of pollutants entering the domestic water supply. Low molecular weight compounds, also known as small molecules, are more likely to infiltrate the domestic water supply. Many of these compounds which are or could be detrimental to health (such as pharmaceuticals and their break-down products, food packaging chemicals and PFAS) are not subject to testing by water regulatory agencies. As there are likely to be hundreds of different types of these chemicals, the difficulty and cost in their detection and monitoring would be considerable and most likely prohibitive. Lough Neagh is surrounded by agricultural and industrial facilities and is a water catchment area for numerous streams and rivers in Northern Ireland. In contrast, the Silent Valley water catchment area is located in the central Mourne Mountains and is devoid of circumscribing industrial / agricultural facilities. At an elevation of between 140 and 240 metres, the Silent Valley water catchment area (WCA) is made up of the reservoirs Ben Cram, Spelga and Silent Valley, each fed from rainfall and the Kilkeel river. It was hypothesised by the inventors of the present application that the biochemical profile of individuals whose domestic water supply was sourced from Lough Neagh would differ from the biochemical profile of individuals whose domestic water supply was sourced from Silent Valley, likely due to the chemical profile of the tap water. Individuals who had a blood and urine test at a Randox Health clinic were partitioned into two groups and geospatially defined by the waterbody source of their tap water (i.e . , the geospatial criterion was either Lough Neagh or Silent Valley WCA). This was achieved using their residential postcodes and Northern Ireland Water’s domestic tap water-source database (https: / / www.niwater.com / water-quality-results / ).

[0039] The concentrations of several biochemicals were found to be significantly different between populations whose domestic water source was Lough Neagh and the populations whose domestic water source was Silent Valley WCA (Table 1). To further support the hypothesis that this was due to the chemical contaminants in the water source, tap water analytical data of key chemical pollutants was retrieved from the Nl Water online database for the period corresponding to that during which the populations were subject to blood and urine testing. The results indicated that the biochemistry of the two populations differed according to the domestic tap water waterbody source and, furthermore, this correlated with the amount of chemical pollutants in the tap water, with Lough Neagh showing greater pollution levels (Figure 7). Although “domestic”, “tap” and “drinking” are used throughout the specification, the described methods can be used for any water used or allocated for drinking. The identification that Lough Neagh is subject to an EPE can also be ascertained using the described methods by comparing biochemical data obtained from groups of individuals residing in different towns and cities in Northern Ireland, and the source of the EPE can be traced accordingly.

[0040] Figure 3 shows that female concentrations of the endocrine biochemicals Follicle Stimulating Hormone and Luteinising Hormone are lower in individuals in Belfast, Lisburn, Coleraine and Portadown, compared to Bangor and Newtownards. This approach used the town and city as a geospatial criterion. Analysis of data in the Nl Water domestic water source database highlighted that Bangor and Newtownards residents derive their tap water from Silent Valley WCA, whereas Belfast, Lisburn, Coleraine and Portadown residents derive their tap water from Lough Neagh. By correlating the biomarker data with possible environmental differences between the populations, such as drinking water sources, this approach identifies that an EPE is occurring by grouping individuals by a geospatial criterion (such as town / city), the source of which can be ultimately traced to a polluted waterbody.

[0041] Outside of water pollution, other types of environmental polluting events can be identified, including radon gas and air pollution.

[0042] Radon is a radioactive element present in certain rock types, is geographically widespread and is known to increase the risk of cancers, especially lung cancer. Indoor radon was declared a human carcinogen in 1987 by the WHO and in 1988 by the United States Environmental Protection Agency (EPA). According to the WHO, radon may be responsible for 3-14% of lung cancer cases, which is considered the second leading cause of lung cancer in tobacco smokers and the leading cause in non-smokers. In addition, radon accounts for around 21 ,000 deaths (2%) from cancer in Europe (Riudavets 2022). Being heavier than the main gaseous constituents of air, radon is known to be concentrated in lower rooms of buildings, especially those which are poorly ventilated or possess cracks / fissures in foundations / walls, and it is individuals in these types of environments who are most vulnerable to radon’s toxic effects. Exposure to radon is gauged by quantifying environmental levels of radon in the air and there are several information sources detailing its concentration levels (e.g. the UK Radon Map and the UK Government supplied Radon Occurrence map provides details of radon concentrations at the kilometre scale level https: / / www.ukradon.org / information / ukmaps). Although these maps provide the individual with guidance to the likelihood and potential extent of radon exposure, especially in radon-rich areas, it is unable to identify the localised build-up of radon concentrations in instances of poorly ventilated buildings and / or buildings over-exposed to radon infiltration due cracks or fissures in foundations and walls. Biochemical indicators of radon exposure such as blood proteins are not prone to this oversight and thus enable the application of the geospatial population methods described herein. Upon application of the geospatial methods described herein, novel biomarkers of high radon concentrations were identified. On a population level, this biochemical data provides a method to identify sources of existing and emergent radon-rich environments using specified locations, enabling management of the toxicant. As used herein, an “emergent radon-rich environment” is a specified location in which radon concentrations increase. On an individual wellbeing level, this may be exploited by the individual observing changes in biochemicals associated with changing levels of radon and mitigating the impact. This may involve physical removal or attenuation of radon, or evacuation of the radon-rich environment.

[0043] Air pollution is a global contributor to ill-health, associated with respiratory disease, cardiovascular disease and cancer, in addition to being a risk factor for all-cause mortality. World Health Organisation (WHO) figures show that practically all of the global population (99%) breathe air that exceeds WHO guideline limits and contains high levels of pollutants. In 2019, air pollution was estimated to contribute to approximately 6.7 million deaths, of which ambient outdoor air pollution in the form of particulates was responsible for approximately 4.2 million deaths (WHO data). The main air pollutants, which result from burning of materials which are mainly hydrocarbon-based, are particulate matter, nitrogen dioxide, carbon monoxide, ozone and sulphur dioxide. Particulate matter is a common proxy indicator for air pollution (WHO: https: / / www.who.int / news- room / fact-sheets / detail / ambient-(outdoor)-air-quality-and-health). Levels of ambient outdoor air pollution in the UK at a postcode level (as gauged by levels 10 pm particulates, 2.5 pm particulates and nitrogen dioxide) was obtained from the Central Office of Public Interest (pollution.org), the data of which was collated and provided by Imperial College London.

[0044] The present invention provides a method by which unknown or unrecognised environmental polluting events (both acute and chronic pollution) can be highlighted enabling measures to be implemented which safeguard human and environmental health. The methods described make use of population biomarker data to benefit the health and wellbeing of individuals and to highlight environmental pollution.

[0045] Accordingly, in a first aspect, the invention provides a method of detecting or alerting to the occurrence of an unrecognised environmental polluting event, comprising: (i) measuring the level of one or more bioindicators in a sample obtained from individuals in a first geospatially defined population; and (ii) comparing the level of the one or more bioindicators in the first geospatially defined population to the level of the same one or more bioindicators in a distinct geospatially defined population, or a control value; wherein a statistically significant difference in the level of the one or more bioindicators between the first geospatially defined population and the distinct geospatially defined population, or the control value, is indicative that the first geospatially defined population has been exposed to an environmental polluting event. It will also be understood that there is provided a use of one or more bioindicators in a sample obtained from individuals in a first geospatially defined population to detecting or alerting to the occurrence of an unrecognised environmental polluting event.

[0046] The term “pollution” is given its usual meaning in the art, and refers to changes, including damage, caused to the environment by substance(s), including harmful substances or natural substances, or waste. As used herein, the terms “environmental polluting event” and “EPE” refer to the presence of a substance or substances in an environment (or release thereof into) that disturbs the ecological / biological homeostasis of the environment at, surrounding or downstream of, the location where the substance(s) have been introduced. By “disruption of ecological / biological homeostasis” we intend that the relative number of organisms and / or the interaction of those organisms within the environment is changed. In other words, there may be an interruption of the steady-state of the environment or a change in the biochemistry or functioning of an individual organism. A “change” may be any alteration including an increase or a decrease. The change may happen instantaneously or substantially instantaneously, or may occur gradually over time for instance over a period of days, weeks, months or years. The term “organism” is given its usual term in the art, referring to any animal, plant, multi-cellular and single-cell life form.

[0047] Accordingly, the environmental polluting event can be any polluting event which triggers such a disruption to the environment. In some embodiments, the environmental polluting event may be any form of release (e.g., spillage) into the environment, deliberate or accidental, of a single or several substances that were previously contained or separate from the environment or were initially specific to a location but subsequently migrate from the location (e.g., downstream of the location). In preferred embodiments, the environmental polluting event may be a contaminated water source, air pollution or radon gas. Examples of environmental polluting events include, but are not limited to, spillage of petroleum oil from a tanker; release of sewage from treatment works into the water course or into agricultural fields; pollution of domestic waste-water by pharmaceuticals, food additives, food waste, cleaning products, personal hygiene products and cosmetics; release of chemicals and waste from factories; leaching from industrial mines; land-fill sites gaseous emissions and leaching; migration of agricultural chemicals (pesticides, herbicides, fungicides, fertilisers) from the their place of application into adjoining locations by means of leeching, run-off and dispersal by air; natural events including radon gas and decay of other radioactive elements, algal blooms, wildfires, volcanic eruptions, dust storms, decomposition; gas and particulate release from incinerators and power stations; gas and particulate release from vehicle engine combustion; and burning and degradation of tyres.

[0048] The term “substance” as used herein refers to the entity causing the pollution, such as a chemical, gas or particulate. The substances involved in such environmental polluting events may be small molecular weight species of approximately less than 1000 Daltons which can also be termed small molecules, oligomeric species, polymeric species including microplastics, particulate matter of various dimensions (e.g., 2.5 microns, 10 microns) commonly derived from burnt or burning matter such as forest fires and vehicular fuel combustion or from the degradation of rubber tyres.

[0049] Food contamination can be considered a further class of environmental pollution. This can occur as both chronic and acute events. For example, contamination of food with pathogenic bacteria such as Escherichia coli (E coli) can result in localised, short-term outbreaks of diarrhoea and as such can be referred to as an acute event caused by environmental pollution (e.g., E. coli connected to mixed salad leaves in the United kingdom, especially South West England https: / / www.gov.uk / government / news / update-as-e-coli-o157-investigation- continues;state-specific and E. coli contamination of walnuts in the United States https: / / www.cdc.gov / ecoli / outbreaks / organic-walnuts-04-24.html). Chronic food pollution can occur from the prolonged or over exposure to food additives. Food additives are largely well regulated and safety concentration thresholds established by thorough testing. The European Food Safety Authority (EFSA) also acknowledges the potential impact of low concentration food additives whose chemical structure of the substance is known, but for which there is limited chemical-specific toxicity data (More, 2019). Microplastics are also a source of chronic food pollution. The methods of the invention can also be used for highlighting acute food pollution and chronic food pollution, especially relating to localised food items which are more likely to be consumed at a specific location (e.g., a town or region) and for which there is prolonged exposure to low concentration chemical food additives of unknown additive / accumulative and long-term toxicity.

[0050] The methods disclosed herein proactively detect or alert to the occurrence of an unrecognised environmental polluting event by monitoring bioindicators / measuring bioindicator data. As used herein, the term “unrecognised” refers to the fact that several environmental polluting events are unknown in that they have not been recognised as an environmental polluting event or detrimental to health. This may be because the substance itself is not known to be a pollutant in the short or long term, or because the environmental polluting event has gone unrecognised (such as an unidentified spillage or release). The environmental polluting event may have gone unrecognised for a period of time, including days, weeks, months or years. In measuring differences in bioindicators, the source of the environmental polluting event can be traced.

[0051] Previously, suitable geographically wide-spread patient cohorts and their associated bioindicator data have not been available for such methods. Until now, patient cohort data has not been available in central databases, is unstandardised and has inferior biochemical comprehensiveness. In many instances, available patient cohort data comprises a substantial proportion of unhealthy or unwell individuals. The availability of geographically wide-ranging in-depth biochemical data from essentially healthy individuals, the data being wholly integrated and standardised enables the present invention to provide a robust method for detecting unrecognised environmental polluting events.

[0052] In the context of any of the aspects of the invention, the term “bioindicator” refers to a measurable biochemical or physiological parameter of an individual. Bioindicator measurement data are the numerical values corresponding to one or more quantified biochemicals or physiological parameters of an individual. Examples of bioindicators include biomarkers and other parameters disclosed herein.

[0053] In preferred embodiments the bioindicators are biomarkers. The term “biomarker” refers to a molecule present in a biological sample obtained from an individual, the concentration of which in said sample may be indicative of an environmental polluting event. Various biomarkers are described herein. “Measuring the level” of a bioindicator refers to a quantitative analysis of that bioindicator, to obtain bioindicator measurement data (also referred to herein as bioindicator data). Measuring the level of, for instance, pulse rate, refers to determining the beats per minute of the heart. Whereas, measuring the level of a biomarker refers to quantifying the amount (i.e. , concentration) of the biomarker present. The skilled person will be familiar with the various techniques which can be employed in the present methods according to any aspect of the invention to measure the level of bioindicators and in particular biomarkers, for instance enzyme-linked immunosorbent assays (ELISA) and other immuno- or probe-based assays, immune-analysers, clinical chemistry, cytometers, PCT, qPCT, mass spectrometry, gas or liquid chromatography, and multiplex approaches using for instance solid state devices or biochips supporting antibodies for detecting certain biomarkers. By way of example, to detect biomarkers, probes (such as antibodies) specific for the biomarkers may be immobilised on a substrate (such as a biochip).

[0054] The level of the one or more bioindicators may be measured in a sample obtained from an individual, i.e., an ex vivo sample. The sample can be any biological sample including blood, serum, plasma, urine, saliva, tears, faecal matter, sweat, hair, breath exudate, skin, and nail. These apply to any of the methods described herein in any aspect of the invention. Preferably, the sample is a blood sample.

[0055] In a given geospatially defined population, the level of one or more biomarkers may be measured in samples obtained from individuals of that population. In some embodiments, the measurements are taken from samples obtained from at least three individuals in the population. In some embodiments, the measurements are taken from samples obtained from each individual in the population. In other embodiments, the measurements are taken from samples obtained from around 100 individuals in the population.

[0056] The level of one or more bioindicators is to be measured. In some embodiments, the level of two bioindicators is measured. In other embodiments, the level of three bioindicators is measured. In other embodiments, the level of four bioindicators is measured. In other embodiments, the level of more than four bioindicators is measured. Preferably, the bioindicators are biomarkers. More preferably, the level of two or more, three or more or four or more biomarkers is measured. The skilled person will understand that any number of bioindicators can be measured. Advantageously, the greater the number of bioindicators measured, the more powerful the method. However, any number of bioindicators may be suitable, including the minimum number of biomarkers required to identify a statistically significant change in the level of the bioindicators.

[0057] The biomarkers measured can be any biological substances known to be present in biological samples. It is preferable that the biomarkers are common clinical chemistry analytes and / or have readily available tests as this reduces the complexity and cost of implementing the described methods. Alternatively, or additionally, an overall biochemical profile may be obtained for each without specifying individual biochemicals or their exact quantities or amounts; for example, the results of gas chromatography analysis, of a biological sample which has been suitably prepared, presents an overall trace or read-out termed the ‘gas chromatogram’. The chromatogram, incorporating an internal standard, could be used in its totality to provide an overall biochemical profile. Processing of several of these profiles for a specific group of individuals, optionally using machine leaning techniques, would provide an average biochemical profile for a specific group of individuals / population which could be used for comparison.

[0058] In some embodiments, the bioindicators are biomarkers selected from the following biomarkers:

[0059] Alpha-1 -acid glycoprotein (AGP)

[0060] Albumin Alkaline phosphatase (ALP)

[0061] Alanine aminotransferase (ALT)

[0062] Apolipoprotein A-l (Apo A-l)

[0063] Apolipoprotein B (Apo B)

[0064] Apolipoprotein C-ll (Apo C-ll)

[0065] Antistreptolysin (ASO),

[0066] Aspartate aminotransferase (AST)

[0067] Calcium

[0068] Creatine kinase (CK)

[0069] Complement C3 (Comp C3)

[0070] Copper

[0071] C-peptide

[0072] Creatinine

[0073] C-reactive protein (CRP)

[0074] D-dimer

[0075] Epidermal growth factor (EGF)

[0076] E-selectin

[0077] Ferritin

[0078] Folic acid

[0079] Follicle stimulating hormone (FSH)

[0080] Free tri-iodothyronine (FT3)

[0081] Free thyroxine (FT4)

[0082] Glial fibrillary acidic protein (GFAP)

[0083] Glutamate dehydrogenase (GLDH)

[0084] Glucose

[0085] Glycated haemoglobin (Hb1Ac)

[0086] High density lipoprotein (HDL)

[0087] Heart fatty acid binding protein (h-FABP)

[0088] Intercellular cell adhesion molecule-1 (ICAM-1)

[0089] Immunoglobulin G g / l (IgG)

[0090] IL-1 a

[0091] IL-1

[0092] IL-2 IL-4

[0093] IL-7

[0094] Insulin

[0095] Iron

[0096] L-selectin

[0097] Low density lipoprotein (LDL)

[0098] Luteinising hormone (LH)

[0099] Magnesium

[0100] Matrix metalloproteinase-9 (MMP-9)

[0101] Oestradiol

[0102] Phosphate

[0103] Potassium

[0104] Progesterone

[0105] Prolactin

[0106] Parathyroid hormone (PTH)

[0107] Resistin

[0108] Sodium

[0109] Thyroid stimulating hormone (TSH)

[0110] Troponin T

[0111] Vascular cell adhesion molecule-1 (VCAM-1)

[0112] Vascular endothelial growth factor (VEGF)

[0113] Vitamin B12

[0114] Vitamin D

[0115] In preferred embodiments, the one or more bioindicators are biomarkers selected from the group consisting of Follicle stimulating hormone, Luteinising hormone, Folic acid, Phosphate, Magnesium, Calcium and Parathyroid hormone.

[0116] In other preferred embodiments, the biomarkers are Follicle stimulating hormone, Luteinising hormone and / or Folic acid. More preferably the biomarkers are Follicle stimulating hormone and / or Luteinising hormone. Even more preferably the biomarkers are Follicle stimulating hormone and Luteinising hormone. In other preferred embodiments, the biomarkers are Magnesium and / or Parathyroid hormone. Preferably, the biomarkers are Magnesium and Parathyroid hormone.

[0117] In other preferred embodiments, the biomarkers are Calcium and / or Parathyroid hormone. Preferably, the biomarkers are Calcium and Parathyroid hormone. Statistically significant differences observed in the levels of these biomarkers may be associated with bone disorders.

[0118] Without being bound by theory, it is possible that these bioindicators are acted on by pollutants acting individually or synergistically. Especially, the balance of various biomarkers, in particular hormones, may be susceptible to disruption by certain pollutants. However, the present methods do not require the identities of these pollutants to be revealed, rather that it is established via a change in bioindicators that a polluting event is occurring. The alert provided by the present methods can prompt institutional bodies to identify the exact source and composition of the environmental polluting event and implement remedial measures.

[0119] Where the biomarkers are derived from female individuals only (e.g., female reproductive hormones), the geospatially defined population is composed of female individuals, and vice versa for males. Where the biomarkers are present in both male and female individuals (e.g., Magnesium, Calcium, Parathyroid hormone), the geospatially defined population can be composed of both male and female individuals.

[0120] Other bioindicators may be measured (in addition to or alternative to biomarkers), including any of the following:

[0121] Age

[0122] Basophil count

[0123] Body mass index (BMI)

[0124] Diastolic blood pressure Estimated glomerular filtration rate (eGFR)

[0125] H. pylori

[0126] Mean corpuscular haemaglobin (MCH)

[0127] Mean corpuscular haemaglobin (MCHC)

[0128] Monocyte count

[0129] Neutrophil count

[0130] Platelet count

[0131] Pulse rate

[0132] Red blood cell mean cell volume (RBC MCV)

[0133] Red blood cell (RBC) count

[0134] Systolic blood pressure

[0135] Total antioxidant status (TAS)

[0136] Total bilirubin

[0137] Total cholesterol

[0138] Total iron binding capacity (TIBC)

[0139] Urine pH

[0140] White blood cell (WBC) count

[0141] Further combinations of bioindicators and their calculated AUCs are seen in Table 5. These combinations of bioindicators were implemented to add further weight to the diagnostic power of the bioindicators disclosed herein. The skilled person will appreciate that the use of greater numbers of individuals in a population will likely lead to increased significance of some bioindicators contributing to a more powerful AUC value.

[0142] In accordance with a first aspect of the invention, there is provided a method detecting an unrecognised environmental polluting event by measuring the levels of one or more bioindicators in a first geospatially defined population, and comparing these with those of a distinct geospatially defined population. The bioindicators as described above and herein are therefore to be measured in a first geospatially defined population. A “population” means three or more individuals. The geospatially defined population may comprise at least three individuals, for example three, four, five, six, seven, eight, nine, ten or more individuals. The geospatially defined population may comprise hundreds, thousands, tens of thousands of individuals. The geospatially defined population may comprise at least three individuals sharing the same geospatial criterion, as discussed herein.

[0143] As used herein, the term “geospatially defined population” refers to a population of individuals defined by a specific location on the Earth’s surface. Geospatial data is data and information referenced to these locations. For the methods described herein, a specific type of geospatial data is termed a “geospatial criterion”. For example, the population may be geospatially defined by a postcode or zip code. In the UK, this may include a postcode area (one or two English alphabet characters e.g. BT for Northern Ireland, NG for Nottingham, L for Liverpool), a postcode district (three to four alphanumeric characters e.g. CT6 for Herne Bay, BT41 for Antrim), and / or a postcode sector (postcode district plus one further number). The national equivalents of the UK postcode system can be applied in the described methods globally, for instance via the United States of America zip code. A population may be geospatially defined by a city, town or village. Individuals sharing the same geospatial criterion thus form a geospatially defined population.

[0144] The profile of the individuals making up a population can be male or female, of any age or ethnicity, medicated or unmedicated and of any health status. It is preferable that each population is composed of individuals of a similar profile. For example, the individuals making up a group are preferably of a similar gender, and / or a similar age range, and / or a similar ethnicity and / or a similar health status and / or similar medication status. This ensures that analytical confoundment due to ethnicity, age, gender, medication status and health status is minimised. In a preferred embodiment, the geospatially defined population is a healthy population, in that it comprises (essentially) healthy individuals, or individuals who are healthy or within the normal / acceptable range thereof. Preferably, the population does not comprise a substantial proportion of unhealthy or unwell individuals. In some embodiments, the geospatial data can be sourced amongst others from work address, home address and telephone tracking data provided by or obtained from the individual, from maps and corresponding co-ordinates and grids (a grid being an area defined by a boundary, usually as squares of varied size e.g. 20 m x 20 m, 100 m x 100 m, 1 km x 1 km), and from online databases . For example, Northern Ireland Water provides a database assigning individual postcodes to the waterbody source of the domestic tap water supply (https: / / www.niwater.com / water-quality-results). Further, the UK Health Security Agency provides a Radon Map (https: / / www.ukradon.org / information / ukmaps). Further, air pollution data is available from several online databases including the Department of Environment and Rural Affairs provide air pollution data (https : / / u k- air.defra.gov.uk / ) and the UK Emissions Interactive Map for air pollutants (https: / / naei.beis.gov.uk / emissionsapp / ).

[0145] In some embodiments, a population may be geospatially defined by (i.e., the geospatial criterion may be) an air quality region, water supply zone, or radon exposure zone. For instance, waterbodies such as lakes and reservoirs which provide domestic tap water in which individuals are grouped according to a common waterbody source (using the publicly accessible databases linking postcodes to waterbody source of tap water) enabling the targeted monitoring of waterbodies for pollution (Figure 1); a geologically-defined area based on the composition of the ground in an area or the concentration in the air of chemical compounds or monatomic gases which volatilise from the ground e.g. radon; a site of a domestic / commercial fuel source such as gas or oil for heat production and power production and a geospatial criterion applied according to an individual’s postcode proximity; a factory or commercial premises from which are provided / made building materials, furniture, housing interiors such as curtains, flooring and carpets, cleaning products and personal care products such as shampoos, soaps, air fresheners, detergents, food-stuffs such as meat, fish, vegetables, pre-packaged and pre-processed foods. Personal care product components can accumulate through excessive use and mis-managed food and drink production can produce edible products that contain pathogens, additives, pesticides / herbicides / fungicides and contaminants which disturb biochemical homeostasis of individuals and be detrimental to health upon their immediate or prolonged ingestion.

[0146] In some embodiments, a population may be geospatially defined by (i.e., the geospatial criterion may be) a house or apartment, a single building, including high-rises and skyscrapers or a group of buildings within a defined area such as a housing / apartment development or estate, a factory, incorporating manufacturing areas with or without offices, a building incorporating one or more offices, a supermarket / hypermarket, a retail park or shopping precinct incorporating several businesses, a single business within the retail park, a hotel or holiday complex, a GP surgery, a clinic, a hospital, an address, a street, a quadrant, a townland, a village, town, a city, a borough, a region (e.g., a recognised National park such as Snowdonia, the Peak District, the Lake District), a county, a country, a recreational venue such as a theatre, discotheque / club, a sports club, a gym, a sports stadium or venue, a music / concert venue, a cafeteria, a mode of transport or vehicle for a group of individuals such as a tram, a bus / coach, a train, an aeroplane, a ferry, cruise liner, a warship, warship support vessels, a submarine, a tanker, or a transport hub such as a coach / bus station, tram station, train station, ferry / port terminal, an airport.

[0147] In some embodiments, a person’s association to a specific location or mode of transport can also be defined using a smart device carried by the individual which is able to be tracked and monitored such as a smart phone or smart watch or a wearable device which has GPS means; in this instance, a person’s association to an area (the amount of time the individual spends in an area / location) can be qualified through quantitative means using a unit of time e.g. 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12 or more hours per day; 10, 15, 20 or more hours per week; 2, 4, 6, 8, 10 or more days per month; 1 , 2, 3, 4, 5, 6 or more months per year; and so on.

[0148] In a preferred embodiment, the individuals within a geospatially defined population are generally settled or permanent members of said population. The skilled person will understand that a number of recently re-located or temporarily present individuals within a population will be tolerated by the method and its statistical analysis.

[0149] In accordance with the invention, the level of the one or more bioindicators measured in the first geospatially defined population are to be compared with the levels of the same bioindicators in a distinct geospatially defined population or a control value.

[0150] Therefore, the described methods involve comparison to a geospatially defined population that is distinct from the first geospatially defined population, i.e., a second (distinct) geospatially defined population. There may be comparison to more than one geospatially defined population that is distinct from the first geospatially defined population, i.e., a second and a third (distinct) geospatially defined population. The method may involve obtaining bioindicator data from the distinct population, or this data may already be available, for instance on databases. Indeed, bioindicator data from both populations may already be available, in which case no measurement step is required and a comparison can be made directly. In any case, the population used for comparative purpose is a geospatially distinct population in that it is defined by a different geospatial criterion. For instance, the first population may be geospatially defined by the postcode area CT6, and the distinct population may be geospatially defined by the postcode area BT41. Any number of geospatial criterion can be used in combination, for instance a postcode area and a postcode district. The skilled person will appreciate that any number of distinct geospatially defined populations can be employed in the present method to make a comparison. For example, the levels of the one or more bioindicators in the first population may be compared to that in a second, third, fourth, fifth, six and so on geospatially defined population which is distinct to the first population.

[0151] In one preferred embodiment, the bioindicator data is compared between three different geospatially defined populations (i.e., a first geospatially defined population and two further (a second and a third) geospatially defined populations distinct from the first geospatially defined population). This is preferable since if two groups of data are compared and both lie within the healthy range and are found to be statistically different, unless one of the groups has a measure of central tendency which is close to the lower or upper range values there would be uncertainty as to which of the groups of data is derived from individuals experiencing a possible environmental polluting event. Advantageously, this facilitates the identification of an environmental polluting event if the bioindicator of one of the populations differs from that of the at least two other populations, the at least two other populations possessing comparable levels of the bioindicator. Confidence in the identification of an environmental polluting event may be further increased if each of two or more bioindicators are identified as having different levels in a first geospatially defined population compared to their concentration in two or more distinct geospatially defined populations, the two or more distinct geospatially defined populations having similar concentrations of each of the two or more biochemicals. Any biochemicals and physiological parameters can be used in the described methods as detailed herein, examples of which are displayed in Tables 1 to 4.

[0152] In another preferred embodiment, there are two geospatially defined populations (i.e., a first geospatially defined population and a second, distinct geospatially defined population from the first geospatially defined population). One example in which two geospatially defined populations can be more confidently used to identify an environmental polluting event is when biomarker measurement values are acquired at successive time-points, as described herein.

[0153] In a more preferred embodiment, the levels of the one or more bioindicators (bioindicator data) is compared between two (preferably three) different geospatially defined populations which use the same laboratory and analysers for sample measurement. Advantageously, doing so allows for potential measurement differences caused by different personnel and / or analysers to be accounted for. Further, this approach can also remove the need for reference ranges or controls.

[0154] Alternatively, the level of the one or more bioindicators measured in the first geospatially defined population may be compared to a control value. The control value may be a standard / normal value expected for a certain bioindicator. Biomarker normal values are well established clinical measurements with concentration ranges which represent a healthy state. The control value may be the levels of the one or more bioindicators measured in the population at a previous point in time. The comparison of a particular bioindicator between populations is readily interpretable if bioindicator level is outside a recognised reference range of the bioindicator.

[0155] Reference ranges are readily available, especially for healthy populations. A laboratory may develop its own reference range for a particular population. The population reference ranges may differ according to age, gender, health status, medication regime and ethnicity. For improved accuracy of the described methods, it is preferable that the biological samples used to derive the population bioindicator data used in the methods are from individuals who have a similar profile (age, sex, health status, socio-demographic status etc) to the individuals from which the reference range was derived. To further increase the accuracy of data comparison, it is preferable that the population data of the geospatially defined populations and the reference range data is derived from individuals who are healthy, as the impact of disease and medication on level of a bioindicator can vary between individuals and potentially impact the precision and analysis of population data.

[0156] In comparing the levels of the one or more bioindicators in a first geospatially defined population to those of a distinct geospatially defined population or a control value, a determination can be made as to whether there are any statistically significant differences between the sets of data. As used herein, the term “statistically significant”, as applied to a specific bioindicator in two (or more) different geospatially defined populations, means that there is a P-value of less than 0.05 when applying a statistical test to compare the measurement values of the specific bioindicator in the two populations. In certain circumstances, for example when the two populations comprise a low number of individuals (e.g. less than 10) then a higher P-value of P <0.10 may be used to assign a statistically significant value. The statistical methods incorporated in the described methods can include the use of data corresponding to bioindicator values of recognised healthy ranges: if one of groups of data incorporated in the method has a measure of central tendency (MCT) such as the mean or median lying outside of the recognised healthy range and the other group MCT lying within the healthy range, and the groups have statistically different MCTs, then the environmental polluting event-impacted geospatially-defined group would correspond to that with a MCT outside of the healthy range. The biochemical concentrations and / or physiological measurements of each of the geospatially defined groups are depicted and analysed using population statistical parameters and methods. The most common parameters are the mean and median, but other measures of central tendency can be used and will be known to those in the art. In one embodiment of the method, the levels of the one or more bioindicators (e.g., concentration(s) of each of biochemicals and / or physiological measurements) of geospatially defined population correspond to a statistical measure, preferably the mean or median. The mean or median of a particular biochemical and / or physiological measurement is computed from measurements obtained from at least three individuals. The individual values used to derive the statistical measure corresponding to each group can be compared using a statistical methodology. A statistically significant difference provides for greater certainty in attributing a difference in the level of a bioindicator between geographically discrete populations and therefore greater certainty in ascribing a possible environmental polluting event. In the described methods herein, a “difference” in the levels of a bioindicator between geospatially defined populations implies a statistically significant difference. Common statistical methodologies that can be used in the described methods for comparing two or more population data sets include t-test, Mann-Whitney, analysis of variance (ANOVA), and Kruskal-Wallis, while for time series analysis change point analysis techniques such as Cumulative Sum & Likelihood Ratio Tests or machine / deep learning can be used, though any suitable statistical methodology can be used and will be known to those in the art. Transformation of data may be required for statistical methodologies that require data to conform to a particular distribution such as the Normal Distribution. Such transformations include Iog10 and Box-Cox transformations.

[0157] Accordingly, where there is a statistically significant difference in the level of the one or more bioindicators between the first geospatially defined population and the distinct geospatially defined population or the control value, this is indicative of an environmental polluting event occurring or having occurred. Based on the present method, in the event of a statistically significant difference, it is likely that an environmental polluting event has or is occurring. “Likely” means that a methodology incorporating quantitative measurement and probability distributions is subject to a degree of uncertainty.

[0158] If the method suggests a possible environmental polluting event, further analysis can be conducted to highlight a possible source of the pollution. For example, to highlight the possible occurrence of a domestic tap water pollution environmental polluting event, the postcodes of individuals making up each of the respective groups of the geospatial criterion can be matched to the water body supplying their domestic tap water and water analysis can be conducted.

[0159] An environmental polluting event can also be identified by observing temporal increases or decreases in the level of a bioindicator of a first geospatially defined population with or without the application of a statistical methodology to compare the group data of each of the years. A graphical depiction associated with this method is shown in the lower graph of Figure 2 in which cities are the geospatial criterion. It is observed that analyte Z, unlike in other cities, increases in London over 3 years suggesting a possible environmental polluting event in London. In this example, a statistical methodology is not used to compare years, although one can be used. Omitting a statistical methodology has the advantage of making the overall methodology less complex.

[0160] Accordingly, in some embodiments, the method of the first aspect involves carrying out the measurement step (step (i)) at a time Ti , and repeating step (i) at a subsequent time T2, and wherein the bioindicator levels of step (ii) are also obtained at Ti and T2, wherein a statistically significant change in the level of the one or more bioindicators in the first geospatially defined population between T1 and T2 and no change in the level of the same one or more bioindicators in the distinct geospatially defined population between T1 and T2 is indicative of the first geospatially defined population being exposed to an environmental polluting event.

[0161] In any aspect of the invention, time point T2 post-dates time point T1. Time points T1 and T2 may be separated in time by a period sufficient to observe changes in the levels of a bioindicator. The time interval between T 1 and T2 may be any period of time, but is preferably one day. Time points T1 and T2 may be separated in time by one day, two days, three days, four days, five days, six days, seven days (one week), two weeks, three weeks, four weeks (one month), three months, six months, nine months, twelve months (one year), two years, three years, four years, five years and so on. Preferably, the interval between times T1 and T2 is one day. Advantageously, such an interval ensures optimal environmental polluting event alerting. However, for chronic polluting events, which are likely to occur over several days, weeks or months, the preferred interval will be greater than one day.

[0162] As with any method incorporating a statistical methodology, the greater the number of sample data-points (individuals in the current instance) the greater the confidence in the results generated by the statistical methodology. Therefore, if there are a low number of sample data-points from day to day then the time interval could be 2 days or greater. For example, if the time interval between T1 and T2 was 1 week (7 days), for the described methods the analysis at T2 would comprise all the data of individuals corresponding to the 7 days following T1. Further time points (i.e., T3, T4, T5 and so on) may also be incorporated.

[0163] At time points T1 and T2, bioindicator data (i.e., the levels of one or more bioindicators) may be measured in the first geospatially defined population. Bioindicator data may also be measured in a distinct geospatially defined population at time point T1, or this data may already be available. The data from both populations in some embodiments may already be available such that the temporal spacing can be incorporated into the method provided that measurements were taken in each population at the same or similar time points. As described herein, measuring the level of one or more bioindicators can be carried out on an ex vivo sample. As described herein, two or three or more geospatially defined populations may be employed in the methods described. Preferably, two or three geospatially defined populations are employed.

[0164] As described herein, the present methods can be implemented daily i.e. the population data sets can be compared each day, population data sets from day- to-day corresponding to different population data, to highlight a possible environmental polluting event. The methods may be repeated especially if there are insufficient data points to conduct a comparative analysis, and / or to ensure optimal alerting to an environmental polluting event.

[0165] The described methods may operate more effectively at a national / country level by collecting patient biological samples and patient data from various areas or locations of a country. A network of countrywide clinics supports take-up of the methods by increasing service-accessibility for individuals while ensuring that the profile of the individuals is diverse e.g. ethnically, socially, economically, hence providing for more robust and rigorous data for analysis. Thus, a further embodiment of the invention describes a method of alerting to the occurrence of an environmental polluting event in which the group geospatial data used for comparison is derived from patient biological samples and physiological measurements and patient data obtained from a country-wide network of dedicated and / or mobile clinics (Tables 1 to 4).

[0166] A mobile clinic can be a temporarily erected structure in place for a defined amount of time, or can be lorry or van-based clinic. The samples obtained at each clinic can be analysed in situ or can be forwarded to a centralised laboratory for analysis. There may be several centralised laboratories, depending upon the size of a country, population density and the number of networked clinics. For example, in the UK, a network of countrywide clinics may be served by four centralised laboratories, one each for Northern Ireland, Wales, Scotland and England. An alternative configuration could have England, possessing a greater population, having at least two centralised laboratories. By using central laboratories for biochemical sample analysis, standardised protocols are more readily adhered to, biochemical analysis is restricted to a smaller pool of analysers, technicians operating the analysers and common test reagent batches can be used, each of which contributes to suppression of variation in biochemical test measurement results. Alternatively, each clinic can incorporate the analytical instrumentation necessary for sample analysis ensuring that the time between sample collection and provision of patient results is minimised and safeguards against possible sample disturbance and biochemical change within the sample which can be caused when samples are being transported. A mixed-model of larger centralised laboratories and individual clinics housing analytical instrumentation is also possible. The clinic houses trained medical personnel such as phlebotomists and nurses, and can also incorporate trained / qualified personnel to effect sample preparation and analysis, if required, although this is not a necessity.

[0167] In some embodiments, the method of the first aspect may be used to determine an appropriate course of action for the population that has been exposed to an environmental polluting event. For example, the environmental polluting event will be managed or brought to an end and / or individuals within the population act or be treated accordingly.

[0168] It will also be appreciated that, in addition to alerting to the occurrence of an environmental polluting event, the presently claimed method can also be used to detect the removal of an environmental polluting event. The environmental polluting event may be known or it may have been alerted to by the present methods. For instance, if the level of the one or more bioindicators returns to a ‘normal’ or reference / control level for a given population, then the method indicates that the impact of the environmental polluting event has ended or subsided. Exposure to industrial and vehicular combustion particulates is a known risk factor of hypertension - if this environmental polluting event is removed or if an individual susceptible to particulate-induced hypertension vacates the polluted area, the hypertension can be mitigated. Often, environmental toxins are not recognised as a threat to environmental ecosystems (i.e., by impacting the wellbeing of individual species of flora fauna and their systemic interaction or to the wellbeing and health of individuals downstream of the impacted environment) if they are found to be at a level / concentration which has been categorised as safe by a recognised authoritative organisation. Toxic threshold concentrations of contaminants in water and food produce may in measurements taken in isolation be within the legally prescribed limits, but over time the cumulative amounts could be detrimental to ecosystems and the wellbeing of individuals.

[0169] Concerning the wellbeing of individuals, during the current studies, the population statistic of several bioindicators were found to be dependent upon pollution exposure and the type environmental polluting event.

[0170] Accordingly, in a second aspect, the invention provides a method of identifying whether an individual has been exposed to air pollution, comprising measuring the amount of one or more of Magnesium and Parathyroid hormone in an ex vivo sample obtained from the individual at time Ti; and measuring the amount of one or more of Magnesium and Parathyroid hormone in an ex vivo sample obtained from the individual at a time T2, wherein a decrease in the amount of Magnesium and / or Parathyroid hormone between T1 and T2 indicates that the individual has been exposed to air pollution. The ex vivo sample obtained at time T1 may be a first ex vivo sample. The ex vivo sample obtained at a time T2 may be a second ex vivo sample. As above, time points T1 and T2 may be separated in time by a period sufficient to observe changes in the levels of a bioindicator. A decrease between T1 and T2 indicates that the individual has been exposed to air pollution between time points T1 and T2.

[0171] It will also be understood that there is provided a use of one or more of Magnesium and Parathyroid hormone to identify whether an individual has been exposed to air pollution. As such, the invention further provides Magnesium and Parathyroid stimulating hormone for use as biomarkers of air pollution. Since these biomarkers are present in both male and female individuals, the method is not limited to use in any particular gender. The biomarkers may be used individually, together or in any two-fold combination i.e., Magnesium or PTH in combination with one or more further bioindicators (preferably biomarkers) herein disclosed. The validity of the described bioindicators as markers of air pollution is supported by the finding that the biomarkers results comparing high pollution to low pollution locations also highlighted blood pressure as significantly raised in high pollution locations - this physiological measurement is an established biomarker of air pollution.

[0172] In some embodiments, the method of the second aspect may be used to determine an appropriate course of action for the affected individual. For instance, an individual exposed to air pollution may be directed towards a specialist clinic or healthcare professional. It may be recommended to limit outdoor activities, to use an inhaler, and so on. In the case of radon exposure, ventilation may be increased or radon-mitigation systems may be employed in areas across the affected population. In extreme cases it may be recommended that the individual re-locates to a less polluted area.

[0173] Accordingly, in a third aspect, the invention provides a method of identifying whether a female individual has been exposed to polluted water, comprising measuring the amount of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid in an ex vivo sample obtained from the individual at a time Ti; and measuring the amount of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid in an ex vivo sample obtained from the individual at a time T2, wherein a decrease in the amount of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid indicates between T1 and T2 that the individual has been exposed to polluted water. The ex vivo sample obtained at time T1 may be a first ex vivo sample. The ex vivo sample obtained at a time T2 may be a second ex vivo sample. As above, time points T1 and T2 may be separated in time by a period sufficient to observe changes in the levels of a bioindicator. A decrease between Ti and T2 indicates that the individual has been exposed to polluted water between time points T1 and T2.

[0174] It will also be understood that there is provided a use of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid to identify whether a female individual has been exposed to polluted water.

[0175] In some embodiments, the female individuals have not been administered hormone replacement therapy or chemical contraceptives, as these could impact certain biomarker concentrations.

[0176] As such, the invention further provides Follicle stimulating hormone, Luteinising hormone, Folic acid and Phosphate for use as biomarkers of tap water pollution for females. The biomarkers may be used individually, together or in any two-fold or three-fold combination. A preferred combination is FSH and LH.

[0177] In some embodiments, the method of the third aspect may be used to determine an appropriate course of action for the affected female individual. For instance, a female individual exposed to polluted water may be directed towards a specialist clinic or healthcare professional. A course of antibiotics or antidotes to bacterial or chemical exposure may be recommended. Drinking water derived from the polluted water source may be avoided until the EPE has been prevented or adequately managed.

[0178] As above, in any aspect of the invention, the sample may be any biological sample, including blood, serum, plasma, urine, saliva, tears, faecal matter, sweat, hair, breath exudate, skin, and nail. However, it is preferred that the sample is a blood sample.

[0179] In addition to the above, the data highlighted several further bioindicators which can be used to identify tap water pollution, radon pollution and air pollution. These are listed in Tables 1 , 2, 3 and 4 and correspond to the measurands described in the examples which have a measurement value with one or more asterisks, indicating statistical significance.

[0180] Any of the methods described herein may be implemented as a one-off event or on a routine basis. For example, the methods can be implemented daily (i.e. , the population data sets can be compared each day, population data sets from day- to-day corresponding to different population data, to highlight a possible environmental polluting event. If within any single geospatially defined population there are insufficient data points for any given bioindicator to conduct a comparative analysis, the method can be implemented once every two days, once every three days, once every four days, weekly, monthly, yearly and so on. Advantageously, regular implementation of any of the methods described herein may result in optimal alerting and detection.

[0181] An advantage of the presently disclosed methods is that the methods do not require prior knowledge of the specific environmental pollutant responsible for a deviation, or difference, in bioindicator levels. The prior art relies heavily on the use of bioindicator levels to monitor already known environmental polluting events. In contrast, the present methods agnostically screen populations for any statistically significant changes in the level of their bioindicators to determine whether an environmental polluting event may be impacting one of the populations. By indirectly inferring such polluting events causing otherwise undetected differences between populations, the present methods proactively enable the detection of unrecognised environmental polluting events, both chronic and acute. The methods can therefore be implemented to stop, prevent and / or minimise the impact of environmental polluting events on the health of populations, individuals and the environment.

[0182] The above-described method may be implemented as a computer-implemented method, using a suitable computing system, for detecting environmental polluting events (EPEs) by analysing physiological or biochemical bioindicator data obtained from a population of individuals and associating deviations in such data with specific geospatial regions or corresponding geospatial groupings. Accordingly, the embodiments described with reference to the method of the first, second or third aspects of the invention are applicable to the computer- implemented methods, computer program products and systems described herein. In particular, the bioindicator measurement data may relate to any of the bioindicators and any of the combinations thereof, disclosed in any of the first, second or third aspects of the invention; the populations and individuals therein may be defined as disclosed in any of the first, second or third aspects of the invention; the samples obtained from individuals of the populations to obtain said bioindicator measurement data may be as disclosed in any of the first, second or third aspects of the invention.

[0183] The computer system and computer-implemented method provides a novel, data- driven approach for identifying unrecognised environmental hazards in a manner that is both proactive and scalable, relying on routinely collected clinical bioindicator data, routine clinical testing, and automated statistical analysis across different geographic regions to identify potential pollution events that may otherwise go undetected by traditional environmental monitoring systems. The system can generate actionable alerts indicative of environmental contamination or exposure. The method may be embodied in software executing on a server, networked computing infrastructure, or cloud-based analytics platform. The method may be carried out on an individual basis in a point-of-care environment.

[0184] The method comprises collecting and processing bioindicator measurement data for a plurality of individuals in a population. The bioindicator measurement data may be obtained from clinical laboratory sources, such as from routine blood, serum or urine tests. The bioindicator measurement data includes data related to any measured bioindicator or biomarker previously disclosed herein for example, but not limited to, concentrations of Follicle stimulating hormone (FSH), Luteinising hormone (LH), Folic acid, Phosphate, Calcium, Magnesium, or other bioindicators that may exhibit sensitivity to physiological changes caused by environmental stressors, including contaminants or pollutants found in air, water, or soil. The bioindicators may, or may not be, be selected on the basis of their responsiveness to environmental exposures, and may result in measurable physiological deviations prior to the manifestation of clinical symptoms or recognition of an environmental polluting event through conventional environmental monitoring.

[0185] Each bioindicator measurement is linked to a specific individual via identifying information such as a patient ID and geospatial data associated with the individual. The geospatial data comprises at least one “location-based attribute” (which may also be referred to as a “geospatial criterion”) associated with the individual as described herein, and includes but is not limited to a postcode area, postcode district, postcode sector, GPS coordinates, residential address, healthcare provider region, known water supply sources, designated air quality zones (e.g., based on EPA or local environmental agency maps), radon concentration zones, administrative districts, or other predefined environmental strata. In some embodiments, more than one geospatial criterion is utilised. There may be overlap such that one individual has several geospatial criterions, which are shared with other individuals. For instance, individuals sharing a housing development geospatial criterion will also share a town geospatial criterion. The computer system described herein in some embodiments may analyse and update bioindicator data in real-time. This data may be used to identify a common geospatial criterion between individuals and ultimately the EPE.

[0186] With reference to Figure 8, the bioindicator measurement data may be stored in a secure database priorto being received S101 by a computing system, forexample an input module of a computing system, for downstream processing and geospatial analysis. The computing system may receive S102, the geospatial data and assign S103, individuals into cohorts or groups based on at least one shared location-based attribute. In other words, individuals sharing a common locationbased attribute are assigned to the same group. A first group of individuals may share a first geospatial criterion / location-based attribute, and a second group of individuals may share a second geospatial criterion / location-based attribute. The individuals may be assigned into any number of appropriate groups.

[0187] The individuals may be assigned to groups automatically by a software module configured to access a database of geographic boundaries, infrastructure networks (such as water supply maps), or government-defined environmental zones. In some examples, the grouping may be dynamic and updated in real time based on current environmental zoning maps or infrastructure data.

[0188] In some examples, instead of the computer system separately receiving bioindicator measurement data for a plurality of individuals and geospatial data for the plurality of data, and then subsequently assigning the individuals to multiple groups, the computer system may receive data that has already been assigned. In this case, the computer system would receive bioindicator measurement data for a first group of individuals all of which share a location-based attribute.

[0189] The method continues by obtaining S104, by the computer system, comparison data. In some examples, the comparison data comprises a control value indicative of a predefined level of one or biomarkers of interest. In other examples, the comparison data comprises data from a different group of individuals to the group of individuals in question which are being analysed.

[0190] Once individuals have been grouped into multiple distinct groups (or if only one group of individuals exists, one group is represented by the control value), a statistical comparison of the bioindicator measurement data is performed to determine whether there are significant differences between the groups. In particular, both the bioindicator measurement data from a first group of individuals and the comparison data (either in the form of bioindicator measurement data from a second group or a control value) comprise a value indicating a level of the one or more bioindicators of interest. The computing system compares S105, the level of the one or more bioindicators in the bioindicator measurement data of the first group with the level of the one or more bioindicators in the comparison data. Here “level” is used interchangeably to mean a “value”. The comparison may be executed by one or more processors of the computer system under the control of a software application or statistical processing engine, which applies one or more statistical tests appropriate to the distribution, nature, and structure of the bioindicator values. Suitable statistical methods may include, but are not limited to: Student’s t-test for comparing means between two groups; Mann-Whitney U test for non-parametric comparison; one-way ANOVA for comparing multiple group means; and Kruskal-Wallis test for non-parametric comparison across multiple groups. These tests may be configured to identify significant differences in the mean, median, dispersion, variance, or other distributional characteristics of the bioindicator measurement data between the groups. The statistical comparison may be conducted on a univariate or multivariate basis, depending on the implementation, and bioindicator values may be normalized or adjusted for covariates such as age, sex, or pre-existing health conditions.

[0191] When the comparison reveals a significant deviation (also referred to as a statistically significant difference or change in one or more biomarker values for a particular group relative to one or more comparator groups, this deviation is interpreted by the system as a signal indicative of a potential environmental polluting event affecting the relevant geospatial region of said particular group. A statistically significant difference may be considered present when a p-value of the result of the comparison is less than a threshold. Thresholds for statistical significance (e.g., p-value < 0.05) may be preconfigured or dynamically adjusted by the computer system.

[0192] Upon determination of a statistically significant difference S106, the computer system generates S107 an output signal (also referred to as an indication) indicating that a group may have been exposed to an EPE. The output signal may be a visual signal and / or an audio signal. For example, the output signal which may include a visual alert on a monitoring dashboard, an electronic message to public health or environmental authorities, or a report containing details of the affected biomarker(s), population location, and / or statistical evidence. As an example, if there is a statistically significant reduction in Folic acid and Follicle stimulating hormone among residents in a postcode associated with a specific water treatment plant, the computer system may generate an output indicating that the water supply in that region has likely been exposed to, or is being exposed to, an environmental polluting event.

[0193] The output of the statistical analysis may be communicated via an electronic interface, which may include a dashboard, report generation engine, or alert system. The alert may be directed to public health officials, environmental monitoring agencies, clinical laboratories, or other stakeholders. The alert may include details of the affected geographic region, the specific bioindicators exhibiting abnormal values, the statistical significance of the findings, and recommended actions such as further investigation or confirmatory environmental testing.

[0194] In some examples, the method includes a temporal component, wherein bioindicator measurement data for a given geospatially defined population is analysed across multiple time points. In this way, the bioindicator measurement data is compared at two or more time points to detect a temporal change in bioindicator levels in one geospatially defined group relative to another. The bioindicator measurement data within a group is compared across at least two different time points to identify a temporal trend indicative of an emerging or resolved environmental polluting event.

[0195] The inclusion of temporal analysis enables the detection of emerging pollution events, chronic exposure trends, seasonal variations, or the resolution of previously identified environmental incidents. The temporal analysis may employ time-series methods such as moving averages, linear regression, time-series regression, or more advanced statistical change point detection techniques to identify shifts in bioindicator distributions over time. The system may be configured to re-analyse stored data periodically as new bioindicator results become available, providing continuous surveillance of environmental impacts on population health.

[0196] If temporal analysis is employed, in some examples, the receiving step S101 may comprise receiving first bioindicator measurement data for the first group of individuals at a first time and a second time. The obtaining step S104 may comprises obtaining comparison data at the first time and the second time. The comparing step S105 may comprise comparing the first bioindicator measurement data of the first group of individuals at the first time with the first bioindicator measurement data of the first group of individuals at the second time, and comparing the comparison data obtained at the first time with the comparison data obtained at the second time. If it is determined that there is a statistically significant difference between the first bioindicator measurement data of the first group of individuals at the first time and the first bioindicator measurement data of the first group of individuals at the second time and there is no statistically significant difference between the comparison data obtained at the first time and the comparison data obtained at the second time then the computer system outputs an indication that the first group of individuals has been exposed to an EPE.

[0197] The computer system which may be used to implement the method described herein may comprise one or more processors, a memory coupled to the processor(s), and one or more databases storing bioindicator measurement data and geospatial data. The system may include any combination of: a data acquisition module for retrieving bioindicator measurement data, a data input module for receiving bioindicator measurement data from external sources such as databases or other devices, a geospatial grouping module, a processing module such as a statistical analysis module, an output module, and a reporting and alert module. The computing system may be networked and may include a data storage module and a reporting interface. The computer system may interface with one or more laboratory information management systems, electronic health records, centralized health data repositories, or environmental databases. Communication with these systems may be facilitated via application programming interfaces (APIs), secure data feeds, or other electronic data interchange protocols. The software implementing the method may be deployed on a cloud-based infrastructure to support scalability and real-time data integration from multiple regions or clinics.

[0198] An advantage of the method, including its computer implementation and the system on which the method is run, is that the method does not require prior knowledge of the specific pollutant responsible for a deviation, or difference, in bioindicator levels. Instead, the method operates agnostically with respect to the causative agent, allowing the computer system to detect previously unrecognized or undocumented EPEs. This represents a significant departure from traditional environmental monitoring systems, which are typically pollutant-centric and rely on direct measurement of environmental media such as air, water, or soil. In contrast, the disclosed system and method infers pollution events indirectly by detecting physiological changes in the affected population using deviations in routine clinical bioindicator measurement data between geospatially defined population groups. By leveraging existing health infrastructure and applying advanced statistical analysis, the system enables early detection of environmental contamination in a manner that is proactive, automated, cost-effective, and scalable. The invention is applicable across multiple environmental media, including water, air, and soil, and is particularly valuable in regions where environmental monitoring infrastructure is limited, delayed, or absent.

[0199] The invention is now described with reference to the following non-limiting examples.

[0200] Bioindicator data was derived from in-clinic physiological measurements and patient blood and urine samples of male and female adults aged 18 to 75 years, collected at Randox Health UK Clinics in Crumlin & Holywood (Nl), Liverpool (Liv) and London (Lon). Biological samples were analysed at centralised laboratories at Randox Health London, Randox Health Liverpool and Randox Clinical Laboratory Services in Antrim. Analysers used for measuring the bioindicators were Randox Imola, Randox Daytona, Randox Daytona Plus, Randox Evolution, Sysmex XS1000i, Roche e601 & e801 , Roche Urisys 1100 and Siemens Immulite 2000XPL For the bioindicators such as BMI, pulse rate and blood pressure, standard means in the art were used for quantification. The age of individuals was recorded.

[0201] The other bioindicators were measured as follows:

[0202] Glucose mmol / l was measured on a Roche Urisys analyser.

[0203] Insulin pmol / l, C-peptide pmol / l, folic acid pg / l (FA), Troponin T pg / ml and Vitamin B12 ng / l were measured on a Roche Cobas analysers.

[0204] Albumin g / l, alkaline phosphatase U / l (ALP), alanine aminotransferase U / l (ALT), aspartate aminotransferase U / l (AST), Apolipoprotein A-l mg / dl (Apo A-l), apolipoprotein B mg / dl (Apo B), C-reactive protein mg / l (CRP), copper pmol / l, creatinine pmol / l, creatine kinase U / l (CK), glutamate dehydrogenase (GLDH) U / l, immunoglobulin G g / l (IgG), iron pmol / l, ferritin pg / l, total bilirubin pmol / l, calcium nmol / l, magnesium mmol / l, phosphate mmol / l, resistin ng / ml, sodium mmol / l, high density lipoprotein mmol / l (HDL), glycated haemoglobin mmol / mol (Hb1Ac), total cholesterol mmol / l, total antioxidant status mmol / l (TAS), total iron binding capacity pmol / l (TIBC) and antistreptolysin O lU / ml (ASO) were measured using a Randox Imola analyser.

[0205] Basophil count 109 / 1, mean corpuscular haemaglobin pg (MCH), mean corpuscular haemaglobin concentration g / l (MCHC), monocyte count 109 / 1, neutrophil count 109 / 1, red blood cells 1012 / 1 (RBC), red blood cell mean cell volume fl (RBC MCV) and white blood cells 109 / 1 (WBC) were measured on a Sysmex XS1000L

[0206] H. pylori U / ml was measured on a Siemen's Immulite 2000XPi analyser. Follicle stimulating hormone IU / I (FSH), lutenising hormone IU / I (LH), oestradiol pmol / l, progesterone nmol / l, free thyroxine pmol / l (FT4), free tri-iodothyronine pmol / l (FT3), intercellular cell adhesion molecule-1 ng / ml (ICAM-1), glial fibrillary acidic protein (GFAP) ng / ml, Heart fatty acid binding protein (h-FABP) ng / ml, D-dimer ng / ml, IL-1 a pg / ml, IL-1 p pg / ml, IL-2 pg / ml, IL-4 pg / ml, IL-7 pg / ml, L- selectin ng / ml, E-selectin ng / ml, epidermal growth factor pg / ml (EGF), matrix metalloproteinase-9 ng / ml (MMP-9), parathyroid hormone pmol / l (PTH), thyroid stimulating hormone mIU / l (TSH), vascular cell adhesion molecule-1 ng / ml (VCAM-1), vascular endothelial growth factor pg / ml (VEGF) and Vitamin D nmol / l were measured on a Randox Evolution analyser using Biochip Array Technology and the test panels Cerebral Array I, Cytokine Array I, Cytokine Array IV, Cytokine Array V, Neurovascular Array, Thyroid Free Array, PTH Assay, Vitamin D Assay and Adhesion Molecule Array.

[0207] Each test was performed according to accompanying Information for Use datasheets provided with each test. Each analyser is used in its standard manner without modification. Patients visited a Randox Health clinic located in Northern Ireland (Holywood and Crumlin), Liverpool and London. Following 24 hourfasting, a blood and urine sample was obtained and physiological measurements and personal data acquired. Blood was obtained by venipuncture of the inner forearm by qualified phlebotomists. The biological samples were analysed within 24 hours of sample obtention.

[0208] Although clinical chemistry, immunoanalysers and cytometers were used in the current study, the concentration of biochemicals can determined using any suitable analytical system, such as gas or liquid chromatography and mass- spectrometry. The skilled person will be highly familiar with the various techniques which can be employed.

[0209] Example 2 - Pollution of Water Bodies Supplyinq Domestic Tap Water

[0210] The preliminary gender-specific analysis comparing blood and urine samples of all individuals with postcodes supplied with tap water sourced from Lough Neagh to all individuals with postcodes supplied with tap water sourced from Silent Valley WCA identified multiple bioindicators that differed in their levels (Table 1).

[0211] An initial population comparative analysis of biomarker concentrations by town / city highlighted differences in follicle stimulating hormone (FSH) and luteinising hormone (LH) in Bangor / Newtownards compared to four other towns and cities (Figure 3 - bars indicate standard error of the mean). Further analysis showed that lower levels of these two major female endocrine biomarkers were associated with towns and cities whose domestic water source is Lough Neagh (Figure 3). The mean concentration levels of FSH and LH in Coleraine were between the levels observed for Bangor / Newtownards and Belfast / Portadown and Lisburn; domestic tap water for Coleraine residents is from the River Bann via Lough Neagh (Figure 4), suggesting that there is less pollution in the River Bann than in Lough Neagh. This might be expected, since water pollutants are likely to be dispersed / filtered on their journey from Loch Neagh to Coleraine via the downstream River Bann. Lough Neagh (Figure 4) supplies 40% of Northern Ireland’s domestic drinking water and is a catchment lake for many Nl rivers. It has been subject to multiple industrial / domestic sewage pollution events, is subject to major agricultural run-off pressure and is increasingly undergoing algal bloom events. As Bangor and Newtownards receive their domestic water form Silent Valley WCA, a reservoir system located in the Mourne Mountains, this water source is not subject to these factors.

[0212] A relative comparison of various parameters is outlined in Table 1. Analysis of biological samples of female populations residing at three locations in Northern Ireland whose tap water is derived from Lough Neagh show no significant differences in the analyte concentrations of folic acid, FSH or LH (Figure 6; Dunmurry N=30, Antrim N=51 , Portadown N=43).

[0213] The Kruskal Wallis analyses of these three locations for various biomarkers were statistically insignificant: Age P=0.7588, BMI P=0.7998, folic acid P=0.2797, FSH P=0.8122, LH P=0.9495. This is concordant with the tap water contaminant analyses data which suggests that Lough Neagh pollution occurs throughout the lough and is non-localised. A similar statistical comparison (one-way Anova or Kruskal Wallis statistic) of locations whose domestic tap water was derived from Silent Valley waterbody-WCA-fed towns / cities comprising Bangor, Newtownards, Ballynahinch and parts of Lisburn indicated no significant differences in folic acid, FSH, LH, oestradiol, progesterone and prolactin. This suggests that town / city- size and / or geographical location has no or minimal impact on biochemical concentrations.

[0214] Figure 7 highlights the greater contamination of domestic tap water originating from Lough Neagh compared to Silent valley WCA. The individual pesticides used to derive the Total pesticide Data are described in the Nl Water public registers (Nlwater.com).

[0215] Figure 3 displays the relatively higher levels of FSH and LH in Bangor and Newtownards (Silent Valley sourced domestic water) compared to Belfast districts, Lisburn districts and Portadown (Lough Neagh sourced water) and Coleraine (Ballinrees reservoir / River Bann fed from Lough Neagh). A data comparison of age-matched females taking oral contraceptives versus females not taking oral contraceptives showed that oral contraceptives reduced the mean concentration of FSH and LH to <4.9 IU / I and <8.0 IU / I, respectively. Female contraceptives, their break-down products and their up-regulation products are present in water courses and their impact on fish physiology is well-established. Furthermore, drinking water disinfection byproducts have been correlated with irregular menstrual cycles and endometrial cancer in females (Deng et al 2022; Medgyesi D.N. et al. 2022).

[0216] Figure 5 shows that in females taking neither hormone replacement therapy (HRT) nor contraceptive medication FSH, LH and folic acid are at a greater concentration in females of menopausal age (aged 45-55 years) whose domestic water is sourced from Silent Valley WCA compared to Lough Neagh. Folic acid levels are also significantly lower in females aged 18 to 44 years whose water is sourced from Lough Neagh; absorption of this essential nutrient is known to be affected by several medicines (Visentin 2014). Inter-town Female Biomarker comparisons according to Water Source

[0217] Louqh Neaqh domestic water: Age BMI and the concentrations of folic acid, FSH,

[0218] LH, progesterone, oestradiol and phosphate of female populations with postcode districts corresponding to Portadown (incorporates Lurgan & Craigavon), Belfast (Dunmurry) and Antrim were compared using Anova / Kruskal-Wallis. For each of the measurands, there was no significant difference between any of the three locations (Figure 6).

[0219] WCA domestic water: Age BMI and the concentrations of folic acid,

[0220] FSH, LH, progesterone, oestradiol and phosphate of female populations with postcode districts corresponding to Bangor, Newtownards, Lisburn and Ballynahinch were compared using Anova / Kruskal-Wallis. For each of the measurands, there was no significant difference between any of the Four locations.

[0221] There is a correlation between domestic drinking water contamination and certain biochemical concentrations in males and females (Tables 1 and 2 and Figure 7). Nl Water Public Register Reports (https: / / www.niwater.com / water-quality-results / ) state that trihalomethanes (THMs) can occur in drinking water as by-products of the reaction of chlorine, used in the water treatment process, with naturally occurring dissolved organic materials. Nickel can occur at very low levels naturally in source waters, but higher amounts could be associated with industrial pollution. Total pesticides are associated within water catchment areas for weed control by agriculture, industry and local authorities. Although not stated in the Reports nitrates are known to be associated with fertiliser run-off into water catchment areas.

[0222] Certain biochemical concentration differences observed between the two populations delineated by the waterbody source of the domestic water supply, Lough Neagh vs Silent Valley WCA (Table 1), is likely due to increased contamination caused by excessive sewage pollution and agricultural run-off.

[0223] Table 1. Biochemicals that exhibited differences depending on the water body supply domestic tap water. Postal code data of individuals matched to domestic water source waterbody (Lough Neagh or Silent Valley WCA), was used as geospatial criterion; Mann-Whitney or t-test was used as the statistical methodology to compare the two geospatially defined groups for females and males.+= mean value, *P<0.10, **P<0.05, ***P<0.01. Italicised Measurand: significant difference for both male and female individuals.

[0224] Example 3 - Radon pollution

[0225] The radon analysis used data from https: / / www.ukradon.org / information / ukmaps; (Contains British Geological Survey materials, UKRI 2022). This data source allocates a radon level to a postcode (1 km grid square) based on the highest radon percentage potential. United Kingdom Health Security Agency defines radon affected areas as those with 1% chance or more of a house having a radon concentration at or above a level of 200 becquerels per cubic metre. A stratified analysis according to gender and domestic water source (Lough Neagh and Silent Valley WCA), showed that environmental radon concentrations do not affect the biochemical concentrations that were affected by water source, namely female FSH, folic acid and LH. The analysis does suggest a potential impact of radon on physiology as highlighted by biochemical concentration differences in Table 2.

[0226] Table 2. Biochemicals that exhibited differences depending on the localised radon concentration. Postal code data of individuals who have a radon potential of concentrations of >1 % vs <1 % was used as geospatial criterion; Mann-Whitney or t-testwas used as the statistical methodology to compare the geospatially defined groups for females and males. *** P<0.01 , **P<0.05, *P<0.10 using Mann-Witney analysis; median values shown.

[0227] Example 4 - Air pollution

[0228] The air pollution analysis used data from addresspollution.org, a service available from from Central Office of Public Interest (COPI), which provides the annual average levels of three pollutants at UK addresses, obtained from a national 20m2resolution model created by Imperial College London (ICL).

[0229] Pollutants measured by the method are particulate matter of 10.0 microns (PM 10), particulate matter of 2.5 microns (PM 2.5) and nitrogen dioxide.

[0230] Every postcode in the UK is assigned a percentile ranking relative to the pollution levels at every other postcode in the UK: the most polluted properties falling into the 99thpercentile, the least polluted into the 0thpercentile. Postal code data of individuals matched to localised air pollution concentrations (>40% vs <5% percentiles) was used as geospatial criterion. For the first statistical analysis, each individual was assigned an air pollution percentile according to address / postcode using the addresspollution.org database then categorised into two air pollution categories >40thpercentile and <5thpercentile, and for the second statistical analysis air pollution categories >20thpercentile and <5thpercentile. The mean listed biochemical concentration changes are consistent with increasing pollution (Tables 3 and 4: 5thto 20thto 40thpercentile).

[0231] Application of logistic regression to assess the ability of biomarker combinations to discriminate >40thpercentile pollution profiles from <5thpercentile profiles using the AUC metric is shown in Table 5 for females and males. These results further supports the use of the biomarkers for identifying individuals exposed to air pollution.

[0232] By using biochemical data of groups of females which have been geospatially defined (i.e., who have been assigned a geospatial criterion) combustion-related pollution was monitored and its increase flagged. Decreases in magnesium and parathyroid hormone and an increase in pulse rate were observed in both females and males and signal air pollution build-up in a geospatially defined area and measures to reduce it could be implemented.

[0233] On an individual level, biochemical analyses which highlight increases / decreases in the concentration of air pollution-related biomarkers such as those listed in Tables 3 and 4, would allow the individual to relocate to a location free of or with lower air pollution levels. Decreases in calcium, HblAc and sodium and increases in iron and TAS were also observed in females and could similarly be used as biomarkers of air pollution (Tables 3 & 5). In males, increases in albumin, creatinine and platelet count and decreases in ALP, IgG, urinary pH and potassium are observed and could be used as biomarkers of air pollution (Tables 4 & 5). Any combination of the measurands (biomarkers) listed in either Table 3 or Table 4 can be used to support the identification of air pollution in females and males, respectively. It was also found that although TAS was not significantly increased in males in areas of greater pollution as computed by the Mann-Whitney test, it proved to have discriminatory power when applied to logistic regression analysis. Males in areas polluted by particulates also exhibit increases in systolic and diastolic blood pressure, an association that is well-established, and thus lends further support to the validity of the applied methodology. Observation over time of the described biomarker increases / decreases in an individual could suggest exposure to air pollutants, water pollutants and radon and empowers the individual with information which can be acted on. Table 3. Female biochemicals that exhibited concentration differences depending on localised air pollution levels. Postal code data of individuals matched to localised air pollution concentrations (>40% vs <5% percentiles) was used as geospatial criterion.

[0234] *** p<0.01 , **p<0.05, * p<0.10; + average of left & right arm.

[0235] Table 4. Male biochemicals that exhibited concentration differences depending on localised air pollution levels. Postal code data of individuals matched to localised air pollution concentrations (>40% vs <5% percentiles) was used as geospatial criterion.

[0236] *** p<0.01 , **p<0.05, * p<0.10; + average of left & right arm. Table 5. Area under the curve statistics (AUC) for biomarker combinations of individuals of the UK according to the pollution percentile of their home address (>40th percentile vs the <5th percentile).

[0237] It has been shown that by analysing geospatially defined populations and their bioindicator data, the identification of unrecognised environmental polluting events is possible. The present methodology can be facilitated by a network of clinics.

[0238] This methodology also allows individuals to actively manage their own wellbeing; by highlighting possible exposure to environmental toxicants through biomarker measurement an individual can implement counter measures to reduce or remove the detrimental health effects of the environmental polluting event by physical removal of the associated toxicant(s), for example by water filtration if the environmental polluting event is polluted domestic tap water, or relocation to a toxicant-free location if the environmental polluting event is air pollution. REFERENCES

[0239] Hanqing X. et al. (2022). Environmental pollution, a hidden culprit for health issues. Eco-Environment & Health, 1 : 31-45.

[0240] Rickard B.P. et al. (2022). Per- and poly-fl uoralkyl substances (PFAS) and female reproductive outcomes: PFAS elimination, endocrine-mediated effects, and disease. Toxicology, 465: 153031.

[0241] Lim C.C. et al. (2023). Harmful algal bloom aerosols and human health. eBiomedicine, 93: 104604.

[0242] More S.J. et al. (2019). Guidance on the use of the threshold of toxicological concern approach in food safety assessment. EFSA Journal 17(6):5708.

[0243] Deng Y-L. et al. (2022). Associations between drinking water disinfection byproducts and menstrual cycle characteristics: a cross-sectional study among women attending an infertility clinic. International Journal of Hygiene and Environmental Health, 241 : 113931 .

[0244] Medgyesi D.N. et al. (2022). Drinking water disinfection byproducts, Ingested nitrate, and risk of endometrial cancer in postmenopausal women. Environmental Health Perspectives, 130(5), https: / / doi.org / 10.1289 / EHP10207.

[0245] Riudavets M. et al. (2022). Radon and lung cancer: current trends and future perspectives. Cancers, 14(13): 3142.

[0246] Visentin M. et al. (2014). The intestinal absorption of folates. Annual Review of Physiology, 76:251-274.

Claims

56CLAIMS1. A method of detecting an unrecognised environmental polluting event, comprising:(i) measuring a level of one or more bioindicators in a sample obtained from individuals in a first geospatially defined population; and(ii) comparing the level of the one or more bioindicators in the first geospatially defined population to the level of the same one or more bioindicators in a distinct geospatially defined population, or a control value; wherein a statistically significant difference in the level of the one or more bioindicators between the first geospatially defined population and the distinct geospatially defined population, or the control value, is indicative that the first geospatially defined population has been exposed to an environmental polluting event.

2. The method of claim 1 , wherein the one or more bioindicators are selected from the group consisting of: Alpha-1-acid glycoprotein (AGP), Albumin, Alkaline phosphatase (ALP), Alanine aminotransferase (ALT), Apolipoprotein A-l (Apo A-l), Apolipoprotein B (Apo B), Apolipoprotein C-ll (Apo C-ll), Antistreptolysin (ASO), Aspartate aminotransferase (AST), Calcium, Creatine kinase (CK), Complement C3 (Comp C3), Copper, C-peptide, Creatinine, C-reactive protein (CRP), D-dimer, Epidermal growth factor (EGF), E-selectin, Ferritin, Folic acid, Follicle stimulating hormone (FSH), Free tri-iodothyronine (FT3), Free thyroxine (FT4), Glial fibrillary acidic protein (GFAP), Glutamate dehydrogenase (GLDH), Glucose, Glycated haemoglobin (Hb1Ac), Heart fatty acid binding protein (h-FABP), High density lipoprotein (HDL), Intercellular cell adhesion molecule-1 (ICAM-1), Immunoglobulin G (IgG), IL-1 a, IL-1 p, IL-2, IL-4, IL-7, Insulin, Iron, L- selectin, Low density lipoprotein (LDL), Luteinising hormone (LH), Magnesium, Matrix metalloproteinase-9 (MMP-9), Oestradiol, Phosphate, Potassium, Progesterone, Prolactin, Parathyroid hormone (PTH), Resistin, Sodium, Thyroid stimulating hormone (TSH), Troponin T, Vascular cell adhesion molecule-1 (VCAM-1), Vascular endothelial growth factor (VEGF), Vitamin B12, Vitamin D,57Age, Basophil count, Body mass index (BMI), Diastolic blood pressure, Estimated glomerular filtration rate (eGFR), H. pylori, Mean corpuscular haemaglobin (MCH), Mean corpuscular haemaglobin (MCHC), Monocyte count, Neutrophil count, Platelet count, Pulse rate, Red blood cell mean cell volume (RBC MCV), Red blood cell (RBC) count, Systolic blood pressure, total antioxidant status (TAS), Total bilirubin, Total cholesterol, Total iron binding capacity (TIBC), Urine pH, and White blood cell (WBC) count.

3. The method of claims 1 or 2, wherein one or more bioindicators are biomarkers, preferably wherein the biomarkers are selected from the group consisting of: Alpha-1-acid glycoprotein (AGP), Albumin, Alkaline phosphatase (ALP), Alanine aminotransferase (ALT), Apolipoprotein A-l (Apo A-l), Apolipoprotein B (Apo B), Apolipoprotein C-ll (Apo C-l I), Antistreptolysin (ASO), Aspartate aminotransferase (AST), Calcium, Creatine kinase (CK), Complement C3 (Comp C3), Copper, C-peptide, Creatinine, C-reactive protein (CRP), D-dimer, Epidermal growth factor (EGF), E-selectin, Ferritin, Folic acid, Follicle stimulating hormone (FSH), Free tri-iodothyronine (FT3), Free thyroxine (FT4), Glial fibrillary acidic protein (GFAP), Glutamate dehydrogenase (GLDH), Glucose, Glycated haemoglobin (Hb1Ac), Heart fatty acid binding protein (h-FABP), High density lipoprotein (HDL), Intercellular cell adhesion molecule-1 (ICAM-1), Immunoglobulin G (IgG), IL-1 a, IL-1 p, IL-2, IL-4, IL-7, Insulin, Iron, L-selectin, Low density lipoprotein (LDL), Luteinising hormone (LH), Magnesium, Matrix metalloproteinase-9 (MMP-9), Oestradiol, Phosphate, Potassium, Progesterone, Prolactin, Parathyroid hormone (PTH), Resistin, Sodium, Thyroid stimulating hormone (TSH), Troponin T, Vascular cell adhesion molecule-1 (VCAM-1), Vascular endothelial growth factor (VEGF), Vitamin B12, and Vitamin D.

4. The method of any one of claims 1 to 3, wherein the one or more bioindicators are biomarkers selected from the group consisting of: Follicle stimulating hormone, Luteinising hormone, Folic acid, Phosphate, Magnesium, Calcium and Parathyroid hormone.

585. The method of claim 4, wherein the biomarkers are Follicle stimulating hormone, Luteinising hormone and / or Folic acid, and wherein the individuals are female individuals.

6. The method of claim 5, wherein the biomarkers are Follicle stimulating hormone and / or Luteinising hormone, and wherein the individuals are female individuals.

7. The method of claim 4, wherein the biomarkers are Magnesium and / or Parathyroid hormone.

8. The method of claim 7, wherein the biomarkers are Magnesium and Parathyroid hormone.

9. The method of claim 4, wherein the biomarkers are Calcium and / or Parathyroid hormone.

10. The method of claim 9, wherein the biomarkers are Calcium and Parathyroid hormone.11 . The method of any one of claims 1 to 10, wherein the geospatially defined population is defined by a postcode area, a postcode district, a geologically defined area, a skyscraper, a sports venue, an entertainment venue, a concert venue, an educational venue, a shipping port, an airport, a train station, a bus station, an apartment block, a university campus, a college campus, an office building, a factory, a department store building, a retail park, an industrial park, a housing development, a village, a town, a city, a county, a region or a country.

12. The method of claim 11 , wherein the geospatially defined population is defined by a postcode area.

13. The method according to any one of claims 1 to 12, wherein the sample is a blood sample or a urine sample.

14. The method according to claim 13, wherein the sample is a blood sample.5915. The method according to any one of claims 1 to 14, comprising carrying out step (i) at a time Ti , and repeating step (i) at a subsequent time T2, and wherein the bioindicator levels of step (ii) are also obtained at T1 and T2, wherein a statistically significant change in the level of the one or more bioindicators in the first geospatially defined population between T1 and T2 and no statistically significant change in the level of the same one or more bioindicators in the distinct geospatially defined population between T1 and T2 is indicative of the first geospatially defined population being exposed to an environmental polluting event.

16. The method according to any one of claims 1 to 15, wherein the environmental polluting event is a contaminated water source, air pollution or radon gas.

17. The method according to any one of claims 1 to 16, wherein step (ii) is carried out using two distinct geospatially defined populations.

18. The method according to any one of claims 1 to 17, wherein the method further comprises the steps of repeating steps (i) and (ii) to detect the removal of the environmental polluting event.

19. A method of identifying whether an individual has been exposed to air pollution, comprising measuring the amount of one or more of Magnesium and Parathyroid hormone in an ex vivo sample obtained from the individual at time T1; and measuring the amount of one or more of Magnesium and Parathyroid hormone in an ex vivo sample obtained from the individual at a time T2, wherein a decrease in the amount of Magnesium and / or Parathyroid hormone between T1 and T2 indicates that the individual has been exposed to air pollution.

20. A method of identifying whether a female individual has been exposed to polluted water, comprising measuring the amount of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid in an ex vivo sample obtained from the individual at a time T1; and measuring the amount of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid in an ex vivo sample obtained from the individual at a time T2, wherein a decrease in the60 amount of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid indicates between Ti and T2 that the individual has been exposed to polluted water.21 . The method of claim 19 or 20, where in the sample is a blood sample or a urine sample.

22. The method of claim 21 , wherein the sample is a blood sample.

23. The method of any one of claims 20 to 22 , wherein the amount of Follicle stimulating hormone and Luteinising hormone are measured.

24. A computer-implemented method for detecting an unrecognised environmental polluting event (EPE), the method comprising:(i) receiving, by an input module, first bioindicator measurement data for a first group of individuals in a first geospatially defined population, wherein the first bioindicator measurement data comprises a first level of one or more bioindicators in a sample obtained from the first group of individuals;(ii) obtaining, by the input module, comparison data comprising a second level of the same one or more bioindicators;(iii) comparing, by a processor, the first bioindicator measurement data of the first group of individuals with the comparison data;(iv) determining, by the processor, whether there is a statistically significant difference between the first level of one or more bioindicators and the second level of the one or more bioindicators; and(v) if it is determined there is a statistically significant difference: outputting, by an output module, an indication that the first group of individuals in the first geospatially defined population has been exposed to an EPE.

25. The method of claim 24, wherein the comparison data comprises second bioindicator measurement data for a second group of individuals in a second geospatially defined population, wherein the second bioindicator measurement data comprises the second level of the same one of more bioindicators in a sample obtained from the second group of individuals.

26. The method of claim 24, wherein the comparison data comprises a control value representing the second level of the same one of more bioindicators.

27. The method of any of claims 24 to 26, wherein the receiving comprises receiving the first bioindicator measurement data from a laboratory information system, database, or clinical record.

28. The method of any of claims 24 to 26, wherein the receiving comprises receiving the first bioindicator measurement data from a measuring device configured to measure the first level of one or more bioindicators in a sample obtained from the first group of individuals.

29. The method of any of claims 24 to 26, wherein the receiving comprises:(i) receiving, by the input module, bioindicator measurement data for a plurality of individuals;(ii) receiving, by the input module, geospatial data associated with each of the plurality of individuals, the geospatial data comprising a location-based attribute for each individual; and(iii) assigning, by the processor, at least some of the plurality of individuals to the first group of individuals based on a first shared location-based attribute.

30. The method of claim 29, when dependent on claim 25, further comprising assigning, by the processor, at least some of the plurality of individuals to the second group of individuals based on a second shared location-based attribute.

31. The method of claim 29 or 30, wherein the location-based attribute is one of: a postcode area, a postcode district, a geologically defined area, a skyscraper, a sports venue, an entertainment venue, a concert venue, an educational venue, a shipping port, an airport, a train station, a bus station, an apartment block, a university campus, a college campus, an office building, a factory, a department store building, a retail park, an industrial park, a housing development, a village, a town, a city, a county, a region or a country, preferably wherein the locationbased attribute is a postcode area.

32. The method of any of claims 24 to 31 :wherein the receiving step comprises: receiving first bioindicator measurement data for the first group of individuals at a first time Ti and a second time T2; wherein the obtaining step comprises: obtaining comparison data from the first time T1 and the second time T2; wherein the comparing step comprises: comparing the first bioindicator measurement data of the first group of individuals at the first time T1 with the first bioindicator measurement data of the first group of individuals at the second time T2; comparing the comparison data obtained at the first time T1 with the comparison data obtained at the second time T2; wherein if it is determined that there is a statistically significant difference between the first bioindicator measurement data of the first group of individuals at the first time T1 and the first bioindicator measurement data of the first group of individuals at the second time T2 and there is no statistically significant difference between the comparison data obtained at the first time T 1 and the comparison data obtained at the second time T2: outputting an indication that the first group of individuals has been exposed to an EPE.

33. The method of any of claims 24 to 32, wherein the comparison comprises a t- test, a Mann-Whiteny U-test, analysis of variance (ANOVA), or a Kruskal-Wallis test.

34. The method of any one of claims 24 to 33, wherein the indication comprises a visual and / or audio indication.

35. The method of any one of claims 24 to 34, wherein a statistically significant difference is present when a p-value of the result of the comparison is less than a predefined threshold.

36. The method of any one of claims 24 to 35, wherein the one or more bioindicators are selected from the group consisting of: Alpha-1 -acid glycoprotein63(AGP), Albumin, Alkaline phosphatase (ALP), Alanine aminotransferase (ALT), Apolipoprotein A-l (Apo A-l), Apolipoprotein B (Apo B), Apolipoprotein C-ll (Apo C- II), Antistreptolysin (ASO), Aspartate aminotransferase (AST), Calcium, Creatine kinase (CK), Complement C3 (Comp C3), Copper, C-peptide, Creatinine, C- reactive protein (CRP), D-dimer, Epidermal growth factor (EGF), E-selectin, Ferritin, Folic acid, Follicle stimulating hormone (FSH), Free tri-iodothyronine (FT3), Free thyroxine (FT4), Glial fibrillary acidic protein (GFAP), Glutamate dehydrogenase (GLDH), Glucose, Glycated haemoglobin (Hb1Ac), Heart fatty acid binding protein (h-FABP), High density lipoprotein (HDL), Intercellular cell adhesion molecule-1 (ICAM-1), Immunoglobulin G (IgG), IL-1ct, IL-1 p, IL-2, IL-4, IL-7, Insulin, Iron, L-selectin, Low density lipoprotein (LDL), Luteinising hormone (LH), Magnesium, Matrix metalloproteinase-9 (MMP-9), Oestradiol, Phosphate, Potassium, Progesterone, Prolactin, Parathyroid hormone (PTH), Resistin, Sodium, Thyroid stimulating hormone (TSH), Troponin T, Vascular cell adhesion molecule-1 (VCAM-1), Vascular endothelial growth factor (VEGF), Vitamin B12, Vitamin D, Age, Basophil count, Body mass index (BMI), Diastolic blood pressure, Estimated glomerular filtration rate (eGFR), H. pylori, Mean corpuscular haemaglobin (MCH), Mean corpuscular haemaglobin (MCHC), Monocyte count, Neutrophil count, Platelet count, Pulse rate, Red blood cell mean cell volume (RBC MCV), Red blood cell (RBC) count, Systolic blood pressure, total antioxidant status (TAS), Total bilirubin, Total cholesterol, Total iron binding capacity (TIBC), Urine pH and White blood cell (WBC) count.

37. The method of claim 36, wherein the one or more bioindicators are biomarkers selected from the group consisting of: Follicle stimulating hormone, Luteinising hormone, Folic acid, Phosphate, Magnesium, Calcium and Parathyroid hormone.

38. The method of claim 37, wherein the biomarkers are Follicle stimulating hormone, Luteinising hormone and / or Folic acid, and wherein the individuals are female individuals.

39. The method of claim 38, the biomarkers are Follicle stimulating hormone and / or Luteinising hormone, and wherein the individuals are female individuals.6440. The method of claim 37, wherein the biomarkers are Magnesium and / or Parathyroid hormone.

41. The method of claim 40, wherein the biomarkers are Magnesium and Parathyroid hormone.

42. The method of claim 37, wherein the biomarkers are Calcium and / or Parathyroid hormone.

43. The method of claim 42, wherein the biomarkers are Calcium and Parathyroid hormone.

44. The method of any one of claims 24 to 43, wherein the environmental polluting event is a contaminated water source, air pollution or radon gas.

45. A computer program product comprising instructions which, when executed by one or more processors, cause the processors to perform the method steps of any of claims 24 to 44.

46. A system for detecting an unrecognised environmental polluting event (EPE) comprising:(i) a data input module, configured to: receive first bioindicator measurement data for a first group of individuals in a first geospatially defined population, wherein the first bioindicator measurement data comprises a first level of one or more bioindicators in a sample obtained from the first group of individuals; and obtain comparison data comprising a second level of the same one or more bioindicators;(ii) a processing module, configured to: compare the first bioindicator measurement data of the first group of individuals with the comparison data; and determine whether there is a statistically significant difference between the first level of one or more bioindicators and the second level of the one or more bioindicators;(iii) an output module, configured to:65 output an indication, if it is determined there is a statistically significant difference that the first group of individuals in the first geospatially defined population has been exposed to an EPE.

47. A computer-implemented method of determining whether an individual has been exposed to air pollution, the method comprising:(i) obtaining a first value of one or more of Magnesium and Parathyroid hormone in an ex vivo sample obtained from the individual at time Ti; and(ii) obtaining a second value of one or more of Magnesium and Parathyroid hormone in an ex vivo sample obtained from the individual at a time T2;(iii) comparing the first value and the second value; and(iv) outputting an indication that the individual has been exposed to air pollution when the comparison indicates that the second value is less than the first value.

48. A computer-implemented method of determining whether a female individual has been exposed to polluted water, the method comprising:(i) obtaining a first value of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid in an ex vivo sample obtained from the individual at a time Ti;(ii) obtaining a second value of one or more of Follicle stimulating hormone, Luteinising hormone and Folic acid in an ex vivo sample obtained from the individual at a time T2;(iii) comparing the first value with the second value; and(iv) outputting an indication that the individual has been exposed to polluted water when the comparison indicates that the second value is less than the first value.

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