System for detecting airborne viruses

Abstract

A system for detecting airborne viruses, the system comprising at least one local area detector, the local area detector comprising: an aerosol collection module arranged to collect particulate matter from an aerosol sample onto a collection chip; an analysis module arranged to detect an amount of virus as part of the particulate matter contained in the collected aerosol sample; and an output module arranged to issue a warning signal when the total virus content exceeds a predetermined threshold.

Description

Technical Field

[0001] The present invention relates to a system and method for detecting airborne viruses. Background Art

[0002] As is well known, outbreaks of airborne viruses (such as the SARS-CoV-2 pandemic) originate from local outbreaks. In most airborne virus diseases, infectivity precedes the symptomatic period. During the so-called incubation period, the outbreak is not yet detected, but the concentration of the virus in the indoor environment may already be very high. In the case of SARS-CoV-2, the incubation period lasts on average for several days. On a time scale of several weeks, a local outbreak may surge and spread in nearby centers, triggering a regional epidemic. If the epidemic is caused by an unrecognized virus (either because the virus is new, e.g., due to a zoonotic event or viral mutation, or because the virus was not anticipated in that geographical region), the epidemic typically will not be detected until enough clinical cases are reported to alert the health authorities. In addition, clinical similarities to more common diseases also contribute to this time lag. Moreover, according to the current state of the art, the identification of an epidemic typically involves the isolation of the pathogen and its genetic sequencing, which can take several weeks. Additionally, it is worth noting that the same delay also occurs during the discovery of viral variants (such as the SARS-CoV-2 Delta variant in December 2020 and the SARS-CoV-2 Omicron variant in November 2021).

[0003] Furthermore, it has also been observed that the main route of infection is air, especially in indoor environments, where a small number of infected individuals in a room can generate concentrations of viral particles sufficient to infect others. They also persist in the air in the form of aerosols.

[0004] The international community is seeking systems that can effectively combat the spread of the virus in the above two scenarios before the epidemic is detected. In the case of a local outbreak, an ideal virus sensor must be able to detect the presence of the virus within a delay window in order to timely indicate the presence of the virus and thus block the spread of the virus. In the case of a regional epidemic typically caused by a new or unanticipated virus, an ideal sensor must be able to detect new, unanticipated, and potentially harmful viruses on a time scale shorter than several weeks. This can contain the spread of the virus at the regional level, mitigate the impact of the spread of the virus, and prevent the spread of the virus from turning into a pandemic.

[0005] Currently, there is no way to reveal undetected local outbreaks and regional epidemics within an effective time period. In fact, current technologies cannot measure the concentration of airborne viruses, transient responses can address the incubation period, and at the same time reliably inform about new, undefined viruses on a time scale shorter than a few weeks. From this perspective, the state-of-the-art virus detection methods all have some drawbacks. In short, PCR-based methods take longer than the incubation period and can only detect known viruses. Immunoassay-based methods are faster than PCR, but significantly less sensitive, and also can only detect known viruses. Finally, cell culture assay-based methods can detect unknown viruses, but this requires several days and specialized laboratory equipment and personnel, making them impractical.

[0006] A system that can rapidly respond to airborne virus detection and monitor unknown viruses at the appropriate time is still lacking. Such a system can be used as a new global surveillance sensor because it can allow local epidemic outbreaks to be blocked at the appropriate time and limit the spread of epidemics caused by unidentified viruses within a regional scope. Summary of the Invention

[0007] The object of the present invention is to provide a system and method for detecting airborne viruses, which system and method overcome the problems of the prior art. The present invention particularly provides a system and method for detecting unknown airborne viruses or variants of known airborne viruses (preferably variants of known airborne viruses), which system and method have a rapid response and, in some embodiments, a near real-time response.

[0008] To this end, the present invention provides a system according to the first claim. The system is arranged for detecting airborne viruses. The system is preferably arranged for detecting unknown airborne viruses and variants of known airborne viruses. The system is preferably arranged for rapidly detecting airborne viruses, such as detecting airborne viruses near real-time. This can provide real-time warnings to block the spread of local outbreaks or inform of the presence of unknown epidemics within a restricted geographical area. The system includes at least one local detector, and preferably includes a plurality of local detectors, as will be further described below. The local detector includes the following modules:

[0009] · An aerosol collection module, which is arranged to collect aerosol samples from the air. The aerosol collection module samples the air around the local detector. Preferably, the local detector is located indoors, and the air sample is thus an indoor air sample. The aerosol sample includes particulate matter such as viruses and dust. The local detector needs to be able to distinguish virus particles from other particles. How the local detector does this will be further explained below. The aerosol collection module is also arranged to aggregate the particulate matter from the aerosol sample onto a collection chip. The collection chip is, for example, a surface on which particles can be collected in a dry manner. Alternatively, the collection chip is a liquid reservoir in which particulate matter is collected in a wet manner. The advantage of providing a wet reservoir instead of a dry collection surface is that more parameters of the particulate matter can be observed, as will be described below.

[0010] · An analysis module, which is arranged to detect the amount of virus, which is part of the particulate matter contained in the collected aerosol sample. The analysis module includes an optical microscope. The optical microscope can be a label-free optical microscope. By providing a label-free optical microscope, one does not have to apply a time-consuming staining procedure that results in a slow response of the local detector. According to an embodiment of the label-free optical microscope of the embodiment, the optical microscope also has the advantage of being able to detect unknown viruses and variants of known viruses, because the detection method does not require genetic information of the virus, such as the DNA sequence of the virus. According to the label-free optical microscope of the embodiment, the optical microscope is arranged to perform the following steps:

[0011] · Determine the geometric parameters and optional dynamic parameters of the particulate matter contained in the aerosol sample. Geometric parameters are, for example, the size and shape of the particle. Dynamic parameters are, for example, the diffusion coefficient of the particle. The dynamic parameter, especially the diffusion coefficient, is particularly advantageous when the collection chip is a liquid reservoir as described above.

[0012] ● Select candidate virus particles from the particulate matter based on the determined parameters. For example, typical geometric and / or dynamic parameters of the virus are considered when selecting. At this stage, one does not need to know which type of virus is detected. One is only interested in determining whether the particle has characteristics indicating a virus. Therefore, preferably, the local detector has a database that has reference parameter values indicating a virus. Preferably, the reference parameter values indicate viruses carried by humans.

[0013] ● Perform optical spectral measurements on the candidate virus particles,

[0014] · For each candidate virus particle, the obtained optical spectrum is compared with a set of predetermined reference optical spectra corresponding to viruses to determine whether the candidate virus particle is a virus. Additionally, at this stage, one does not need to know which type of virus is detected. One is merely interested in determining whether the particle has characteristics indicative of a virus. Thus, preferably, the local detector has a database that has reference optical spectra indicative of viruses. Preferably, the reference optical spectra indicate viruses carried by humans.

[0015] · Determine the quantity (number) of the detected virus based on the comparison step, i.e., the "total viral content" (TVC) in the aerosol sample.

[0016] · An output module, wherein the output module is arranged to emit a warning signal when the TVC exceeds a predetermined threshold.

[0017] Infected individuals in a room can release viruses through breathing, speaking, coughing, and sneezing. Additionally, some individuals known as superspreaders are more likely to release viruses in their exhaled breath. It is known in the literature that a small fraction of the exhaled viruses remain volatile and are distributed in the ambient air. When an infected individual is near the local detector, such as in the same room as the local detector, these viruses are collected by the system in the same room or environment. Thus, an increase in TVC may indicate the presence of an infected individual or a so-called "superspreader". Subsequently, it can also perform successive biological analyses on the collected virus samples (whether from aerosols or relevant populations). For example, virus sequencing is used to identify new variants.

[0018] According to an embodiment of the present invention, the system as described above is further configured to classify the detected viruses according to their virus families (such as the coronavirus family or the influenza virus family). Preferably, for this purpose, the collection chip of the aerosol collection module includes predetermined regions, each of which is functionalized with virus receptors of a specific virus family. Preferably, the optical microscope is also arranged to perform the following steps:

[0019] · Calculate the quantity of the detected viruses in each predetermined region in order to determine the "family viral content" (FVC) in the aerosol sample.

[0020] The advantage of this embodiment is that it can classify the detected viruses according to their virus families without the need for specific gene information of virus variants. People only use virus receptors that have binding affinity with common virus families. Based on this family classification, people can consider the potential hazards of different virus families before issuing a warning signal. For example, people can set a higher FVC threshold for virus families with less harm. According to an embodiment of the present invention, the output module is also arranged to issue a warning signal when the FVC of a predetermined virus family exceeds a predetermined virus content threshold for the said virus family. In addition, information about the virus family allows the adoption of the most appropriate countermeasures (for example, taking appropriate swab tests for the involved personnel, recommending isolation or self-observation, such as wearing protective masks, etc.).

[0021] According to an embodiment of the present invention, the aerosol collection module includes a "condensation growth tube" (CGT). During the collection stage of aerosol particles (which occurs in the aerosol collection module), it is important that the collection process maintains the integrity of the virus particles. A promising method to maintain the said integrity is to use the well-established CGT technology, which allows gentle sampling by growing water droplets around each collected particle. According to an embodiment of the present invention, a size-selective cyclone can also be implemented at the top of the CGT. The size-selective cyclone selects particles with sizes smaller than a cutoff value. It allows the cutting off of large particles that may interfere with the measurement.

[0022] According to an embodiment of the present invention, the analysis module directly performs analysis on the collection chip. For example, compared with an analysis module that requires transferring the sample from the collection chip to the analysis module, this ensures that fewer particles are lost from the sample. Therefore, this embodiment allows substantially all of the sample to be used for analysis, which achieves better virus detection. This embodiment improves the overall virus detection sensitivity.

[0023] According to an embodiment of the present invention, the analysis module performs the step of selecting candidate virus particles and / or the step of determining TVC by means of Artificial Intelligence (AI). This enables fully automated detection, rapid response, and interconnection between different local detectors for continuous learning of how to identify which particles are viruses and which are not. Preferably, an encoder / decoder algorithm relying on semantic segmentation performs automatic particle detection on the acquired microscope images. Thereafter, these detections are preferably input into an algorithm that detects regions with higher intensity of these particles to extract geometric parameters and optional dynamic parameters for each particle and their optical spectra. Using these parameters, the algorithm performs automatic optical spectrum analysis and calculates the TVC index, for example, using PCA or a regression model. Additionally, when it is necessary to classify the virus family, based on image classification, a second AI algorithm automatically counts the viruses related to their receptors and calculates the FVC index.

[0024] According to an embodiment of the present invention, the geometric characteristics of the particulate matter include the shape and / or size of the particle. According to an embodiment of the present invention, the dynamic characteristics of the particulate matter include the diffusion coefficient of the particle.

[0025] According to an embodiment of the present invention, the analysis module performs the step of selecting candidate virus particles by selecting these particles having geometric parameters and optional dynamic parameters adapted to these viruses as candidate virus particles. The typical size range for viruses is between 50 nm and 200 nm. In fact, due to the diffraction limit of light, it is impossible to optically measure these sizes. Particles smaller than about 200 to 300 nm will appear to have the same size under a microscope. One can only select particles with sizes below this limit and thus be regarded as candidate virus particles. Alternatively, one can use other more complex methods, such as "Optical Signatures of Small Nanoparticles in a Conventional Microscope" by Patterson 2008 that utilizes caustic signals. Generally speaking, according to this embodiment, if the size can be attributed to particles located within the range between 50 nm and 200 nm (i.e., the typical size range of viruses, where such range can be adjusted to include larger viruses), then the particle is confirmed as a candidate virus particle.

[0026] According to an embodiment of the present invention, the analysis module performs a comparison step based on a reference optical spectrum obtained by simulation (such as Mie scattering simulation) or by experiment. Alternatively, the analysis module performs the comparison step based on unsupervised learning of the reference optical spectrum, preferably using principal component analysis (PCA).

[0027] According to an embodiment of the present invention, the analysis module normalizes the measured spectrum of the candidate virus particles relative to the normalized spectrum measured from standard particles spotted at different positions on the same chip. Such an operation allows to solve the problem that the absolute spectrum of the particles cannot be directly measured due to the inherent inhomogeneity of the system (such as the instability of the light source, the presence of optical aberrations, the alignment differences of different system components, for example, the position of the chip relative to the optical path). Therefore, the normalized spectrum must be acquired each time the spectrum of the particles is measured. Normalizing the particle spectrum by the normalized spectrum allows to eliminate these inhomogeneities, thus enabling a continuous comparison between the normalized measured spectrum and a predetermined reference spectrum that has undergone the same normalization process. The standard particles used to generate the normalized spectrum can preferably be spherical polystyrene beads with highly uniform size and shape, such as NIST-traceable size standard monodisperse polystyrene spheres. These particles are very stable and reusable, which makes them an ideal standard reference material for obtaining the normalized optical spectrum.

[0028] According to an embodiment of the present invention, the collection chip is a collection surface on which particles are collected in a dry manner. Alternatively, the collection chip is a liquid collection container that receives the particles as explained above. In the latter alternative, preferably, the analysis module takes into account the dynamic parameters of the particles (such as the diffusion coefficient). According to an embodiment of the present invention, the collection chip includes a hydrophilic region and a hydrophobic region. This enables the transfer and concentration of aerosol particles in a specific location on the collection chip for easy detection and characterization.

[0029] According to a first embodiment of the present invention, the optical microscope in the analysis module is a "hyper-spectral enhanced dark-field" (HSEDF) microscope. The HSEDF microscope preferably operates in a transmission mode. According to an embodiment of the present invention, the analysis module performs the step of collecting the optical spectrum measurement for the candidate virus particles by obtaining the optical spectrum as a scattering spectrum. Preferably, the acquisition of the scattering spectrum is included in the above-mentioned hyper-spectral enhanced dark-field technique, which measures the scattering spectrum for each pixel (and thus for each particle).

[0030] According to a second embodiment of the present invention, the optical microscope in the analysis module is a "hyper-spectral bright-field" (HSBF) microscope. The HSBF microscope is preferably operated in a reflection mode. According to an embodiment of the present invention, the analysis module performs the step of performing optical spectral measurement on candidate virus particles by obtaining an optical spectrum as a reflection spectrum. Preferably, the collection chip of the aerosol collection module includes nano-scale cavities preferably fabricated by focused ion beam. If the particles fill the nano-scale cavities, the optical signal (such as the reflection spectrum mentioned above) from the cavities will change due to the principle of fluctuating optics. Preferably, the nano-scale cavities have dimensions and shapes comparable to the size and shape of the virus. Preferably, the nano-scale cavities have a certain size, for example, a diameter between 100 nm and 1 μm, so that typical viruses can enter the nano-scale cavities while excluding larger particles. Preferably, hydrophilic regions are located at positions corresponding to the nano-scale cavities. Not only inside, but also in the peripheral regions of this area. Droplets containing (virus) particles reaching the collection chip will preferentially select this area. When the droplet dries, it releases the particles into the nano-scale cavities, where the particles can be detected.

[0031] According to an embodiment of the present invention, a region, i.e., a geographical region, is monitored by means of a plurality of local detectors. Preferably, the plurality of local detectors are interconnected in a regional network. Preferably, the system is configured to correlate the TVC and FVC from different local detectors. For example, in this way, the dynamic evolution of the epidemic situation within a geographical region can be tracked.

[0032] According to an embodiment of the present invention, the TVCs of the local detectors in the regional network are accumulated into a "regional TVC" (RTVC), and the system is arranged to issue a warning signal when the RTVC exceeds a predetermined threshold. According to an embodiment of the present invention, the FVCs of each virus family of the local detectors in the regional network are accumulated into a "regional FVC" (RFVC) of each virus family, and the system is arranged to issue a warning signal when the RFVC of a predetermined virus family exceeds a predetermined threshold of the regional virus content of the virus family.

[0033] Another object of the present invention is to provide a method for detecting (preferably in real time) airborne viruses, preferably unknown airborne viruses or variants of known airborne viruses, more preferably variants of known airborne viruses. The method includes using the system as described above.

[0034] As described above, the system is preferably arranged for the rapid detection of airborne viruses, e.g., for the near real-time detection of airborne viruses. The system can be regarded as an artificial lung with a flow rate similar to our respiratory system. The reference "warning" dose may be the infectious dose, which is known in the literature to be approximately a few hundred to a few thousand virions (virions, i.e., infectious viruses). On the other hand, the present system and the related detection method can, in principle, detect individual virus particles. However, for statistical robustness and reliable AI operation, one can consider that a good target number of collected virus particles is approximately between 100 and 1000, i.e., lower than (or in any case, of the same order of magnitude as) the infectious dose. Thus, the present system can, in principle, detect the presence of airborne viruses before the inhaled dose becomes infectious. We can imagine the situation where people enter a room with a viral concentration already present in the air. Once inside, our sensor starts "breathing": it can give a warning signal before the viral dose inhaled by a human becomes infectious. In any case, the system can be always on and continuously monitor the presence of viruses in the environment. To give some numbers, one can refer to Lednicky et al., "Viable SARS-CoV-2 in the air of a hospital room with COVID-19 patients" (2020), where it was measured that in a hospital room with two COVID-19 patients, there were approximately 16÷94 virus particles per liter, of which approximately 6÷74 were viable virus particles per liter. These viruses are evenly dispersed in the air: they are very small and thus the particles have strong mobility and can remain suspended in the air for a long time (several hours). For example, by using an aerosol sampling technique with a sampling rate of 1.5 liters / min, one can, in principle, collect the target number of particles between approximately 2 and 20 minutes. Then, the AI analysis processes the images almost immediately and feeds back the number of particles that may be viruses. Thus, it can be said that the current system is capable of giving an alarm within an effective time to prevent further spread. This time is much faster than the gold standard method of PCR and has further advantages over immunoassay or cell culture assay. In an embodiment, based on the concept of the infectious dose and the possibility of blocking the virus replication (or transmission) cycle, the system and the related detection method can be considered real-time. Considering the possibility of detecting any virus present in the environment, the system and the related detection method can be considered near real-time detection according to the concentration of virus particles in the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a schematic view of a local detector according to an embodiment of the present invention, where the collection chip is a collection surface for collecting particles in a dry manner.

[0036] Figure 2a andFigure 2b Side views and top views of collection chips used in local detectors of Figure 1 are shown respectively, where the collection chip is suitable for an HSEDF microscope.

[0037] Figure 3a and Figure 3b Side views and top views of collection chips of local detectors similar to the local detector shown in Figure 1 are shown respectively, where the HSEDF microscope will be replaced by an HSBF microscope, and where the collection chip is suitable for an HSBF microscope.

[0038] Figure 4 is a schematic diagram of a local detector according to an embodiment of the present invention, where the collection chip is a liquid collection reservoir for collecting particles.

[0039] Figure 5a and Figure 5b Side views and top views of collection chips used in the local detector shown in Figure 4 are shown respectively, where the collection chip is suitable for an HSEDF microscope.

[0040] Figure 6a and Figure 6b Scanning electron microscopy (SEM) images of particulate matter collected with virus-like particles (VLPs) and optical spectral measurements of candidate virus particles including VLPs are shown respectively. Detailed Description

[0041] Figure 1 and Figure 4 show an embodiment of a system for near-real-time detection of unknown airborne viruses according to the present invention. The system is capable of providing real-time warnings to block the spread of local outbreaks or to inform of the presence of an unknown epidemic situation within a restricted geographical area. The system includes at least one local detector 1. The local detector 1 includes the following modules: an aerosol collection module 2, an analysis module 7, and an output module 12.

[0042] The aerosol collection module 2 is arranged to collect an aerosol sample from the air 3. The aerosol sample includes particulate matter (such as viruses and dust). The aerosol collection module 2 is also arranged to aggregate the particulate matter from the aerosol sample onto a collection chip 4. The collection chip is, for example, a surface on which particles can be collected in a dry manner as shown in Figure 1 . Alternatively, the collection chip 4 is one in which particles are collected in a manner as shown in Figure 4The liquid reservoir 6 for collecting particulate matter in the wet mode shown. The aerosol collection module 2 includes a "condensation growth tube" (CGT) 23 for collecting particles.

[0043] The analysis module 7 is arranged to detect the amount of virus that is part of the particulate matter contained in the collected aerosol sample. In Figure 1 the dry collection embodiment shown, the collection surface 5 is transferred from the collection module 2 to the analysis module 7. In other embodiments not shown in this figure, instead of transferring the collection chip, the analysis is performed directly on the collection module by the analysis module, thus creating a more integrated system. In Figure 4 the wet collection embodiment shown, the liquid reservoir 6 is fixed to the analysis module and is in fluid communication with the aerosol collection module 2 via an inflow tube 8. By means of a pump 9 connected to the liquid reservoir 6 through an outflow tube 10, the liquid and the sample contained in the liquid are suctioned from the aerosol collection module 2 towards the liquid reservoir 6 via the inflow tube 8. The analysis module includes an optical microscope 11. Figure 1 and Figure 4 the optical microscope shown is a "hyperspectral enhanced dark field" (HSEDF) microscope. The collection chip 4 for such a microscope is shown in FIGS. 2 and 5. The collection chip 6 shown in FIG. 3 is suitable for Figure 1 or Figure 4 a "hyperspectral bright field" (HSBF) microscope not shown in []. Such an HSEDF microscope is known in the prior art and includes: an illumination source 13 that emits light 17 towards the sample; a microscope objective 14 that receives the light 18 after interacting with the sample; an optical filter 15 that receives the light 19 from the objective; and a camera 16 that receives the light 20 that has passed through the optical filter 15 and has been optically filtered by the optical filter 15 for optical spectral measurement. The optical microscope is arranged to perform the following steps:

[0044] ● Determine the geometric parameters and optionally the dynamic parameters of the particulate matter contained in the aerosol sample. Geometric parameters are, for example, the size and shape of the particles. Dynamic parameters are, for example, the diffusion coefficient of the particles. Dynamic parameters, especially the diffusion coefficient, are particularly relevant when the collection chip 4 is the liquid reservoir 6 as described above.

[0045] ● Select candidate virus particles from the particulate matter based on the determined parameters. For example, typical geometric and /

[0046] or dynamic parameters of the virus are considered during the selection. At this stage, one does not need to know which type of virus is detected. One is only interested in determining whether the particle has characteristics indicative of a virus. Therefore, the local detector 1 has a database (for example, a database associated with the camera 16),

[0047] The database has reference parameter values indicative of a virus.

[0048] ● Perform an optical spectroscopic measurement on the candidate virus particles, preferably mediated by the optical filter 15. The light 19 entering the optical filter 15 is shown as including a mixture of multiple frequencies. The light 20 exiting the optical filter 15 and entering the camera 16 is shown as separate frequency bands (where the darker light represents light with a shorter wavelength than the brighter light), thereby indicating that the light has passed through the optical filter for performing an optical spectroscopic measurement.

[0049] ● For each candidate virus particle, compare the obtained optical spectrum with a set of predetermined reference optical spectra corresponding to the virus,

[0050] to determine whether the candidate virus particle is a virus. Additionally, at this stage, one does not need to know which type of virus has been detected.

[0051] One is only interested in determining whether the particle has characteristics indicative of a virus.

[0052] ● Based on the comparison step, determine the quantity of the detected virus, i.e., the "total virus content" (TVC) in the aerosol sample.

[0053] The analysis module 7 performs the steps of selecting candidate virus particles and / or determining the TVC mentioned above by means of artificial intelligence.

[0054] The output module 12 is arranged to issue a warning signal when the TVC exceeds a predetermined threshold. It is well known that infected individuals can release viruses through breathing, speaking, coughing, and sneezing. Additionally, some individuals known as superspreaders are more likely to release viruses in the air they exhale. It is known from the literature that a small fraction of the exhaled viruses remain volatile and are distributed in the ambient air. When an infected individual is close to the local detector, for example, in the same room as the local detector, these viruses are collected by the system in the same room or environment. Therefore, an increase in the TVC may indicate the presence of an infected individual or a so-called "superspreader".

[0055] The local detector 1 as described above is also configured to classify the detected viruses according to their virus families, such as the coronavirus family or the influenza virus family. For this purpose, the collection chip 4 of the aerosol collection module 2 includes predetermined regions 21a, 21b, 21c, each of which is functionalized with virus receptors of a specific virus family. Such functionalization is shown in FIGS. 2, 3 and 5. In FIGS. 2 and 3, each virus family includes two circular regions provided with dedicated receptors. In FIG. 3, each virus family includes three circular regions provided with dedicated receptors. However, the number of regions is not critical for the present invention. In FIG. 3, the circular regions are disposed within wells 22. The optical microscope 11 is arranged to perform the following steps:

[0056] · Calculate the number of viruses detected in each predetermined region in order to determine the "family virus content" (FVC) in the aerosol sample.

[0057] Figure 6a The SEM image of shows the particulate matter (PM) collected on the collection chip by the aerosol collection module within 10 minutes in an environment doped with VLP. The particles are well separated and distributed above the surface. The VLP is perfectly circular and has typical size characteristics (100 nm in this example). There are also other PM particles in the air sample, which include particles with a larger size than the VLP, particles with a smaller size than the VLP, and particles with a similar size to the VLP but with a different shape and composition (and thus a different refractive index) from the VLP. The different sizes of the particles can identify candidate virus particles, such as including VLP and other PM with a similar size to the VLP. Figure 6b The typical scattering spectra measured by HSEDF are shown in the chart of (larger particles are not shown because their spectra are very different, with a scattering intensity of one or more orders of magnitude). Smaller particles exhibit a lower scattering intensity. PM with similar sizes have different spectral shapes (e.g., higher scattering intensity in the near-infrared region). This enables the system to select viruses from other candidate virus particles, which is VLP in this example.

Claims

1. A system for detecting airborne viruses, the system comprising at least one local detector, the local detector comprising: ● An aerosol collection module arranged to collect an aerosol sample from the air, the aerosol sample comprising particulate matter such as viruses and dust, and further arranged to aggregate the particulate matter from the aerosol sample onto a collection chip, · An analysis module arranged to detect the amount of virus, which is part of the particulate matter contained in the collected aerosol sample, the analysis module comprising an optical microscope arranged to perform the following steps: · Determine the geometric parameters and optionally the dynamic parameters of the particulate matter contained in the aerosol sample, · Select candidate virus particles from the particulate matter based on the determined parameters, · Perform optical spectral measurements on the candidate virus particles, · For each candidate virus particle, compare the obtained optical spectrum with a set of predetermined reference optical spectra corresponding to viruses in order to determine whether the candidate virus particle is a virus, and · Determine the number of viruses detected based on the comparison step, i.e., the "total virus content" (TVC) in the aerosol sample, · And an output module, wherein the output module is arranged to issue a warning signal when the TVC exceeds a predetermined threshold.

2. The system according to claim 1, the system further configured to classify the detected viruses according to their virus families, such as the coronavirus family or the influenza virus family, The collection chip of the aerosol collection module comprises predetermined regions, each of the predetermined regions being functionalized with virus receptors of a specific virus family, and ● Among them, · Wherein the optical microscope is further arranged to perform the following steps: · Calculate the number of viruses detected in each predetermined region in order to determine the "family virus content" (FVC) in the aerosol sample. The analysis module performs the analysis directly on the collection chip.

3. The system according to any one of the preceding claims, wherein, The analysis module normalizes the measured spectra using normalized spectra measured from standard particles spotted at different positions on the same collection chip, and the normalized spectra are then compared with the reference spectra that have undergone the same normalization process, and the standard particles used to generate the normalized spectra are preferably highly uniform monodisperse spherical polystyrene beads.

4. The system according to any one of the preceding claims, wherein, The collection chip is a collection surface on which particles are collected in a dry manner.

5. The system according to any one of the preceding claims, wherein, The collection chip is a liquid collection container in which the particles are received.

6. The system according to any one of the preceding claims 1 to 4, wherein, The optical microscope in the analysis module is preferably a "hyperspectral enhanced dark field" (HSEDF) microscope operating in transmission mode.

7. The system according to any one of the preceding claims, wherein, The analysis module performs the step of collecting optical spectral measurements for the candidate virus particles by obtaining an optical spectrum as a scattering spectrum.

8. The system according to claim 7, wherein, The optical microscope in the analysis module is preferably a "hyperspectral bright field" (HSBF) microscope operating in reflection mode.

9. The system according to any one of the preceding claims 1 to 6, wherein, ​ 10. The system according to claim 9, wherein, The analysis module performs the step of performing an optical spectroscopic measurement on the candidate virus particles by acquiring an optical spectrum that is a reflection spectrum.

11. The system according to any one of the preceding claims 9 to 10, wherein, The collection chip of the aerosol collection module includes nanoscale cavities preferably fabricated by focused ion beam.

12. The system according to any one of the preceding claims, wherein, A region is monitored by means of a plurality of local detectors, and the plurality of local detectors are preferably interconnected in a regional network.

13. The system according to claim 12, wherein, The TVCs of the local detectors in the regional network are cumulated as "regional TVC" (RTVC), and the system is arranged to issue a warning signal when the RTVC exceeds a predetermined threshold.

14. The system according to claim 13 in combination with claim 2, wherein, The FVCs of each virus family of the local detectors in the regional network are cumulated to the "regional FVC" (RFVC) of each virus family, and the system is arranged to issue a warning signal when the RFVC of a predetermined virus family exceeds a predetermined threshold of the regional virus content of the virus family.

15. The system according to any one of the preceding claims, wherein, The optical microscope is a label-free optical microscope.

16. The system according to any one of the preceding claims, wherein, The step of determining the geometric parameters and optionally the dynamic parameters of the particulate matter contained in the aerosol sample and selecting candidate virus particles from the particulate matter based on the determined parameters is accomplished by selecting particles having a size below 300 nm, preferably below 200 nm, more preferably in the range between 50 nm and 200 nm from the particulate matter.

17. A method for detecting an unknown airborne virus or a variant of a known airborne virus, preferably for detecting a variant of a known airborne virus, the method comprising using a system according to any one of the preceding claims.

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