Medical accessibility analysis method and system for urban waterlogging emergencies

Abstract

The present invention discloses a medical accessibility analysis method and system for urban waterlogging emergencies, belonging to the field of urban planning technology. The method includes: obtaining road network data and waterlogged road section damage data of the study area, and constructing a transportation network; generating Thiessen polygons with the nodes of the transportation network as the center, coupling the total population and the supply capacity of medical institutions within the Thiessen polygons with the nodes of the transportation network; calculating the reachable node set of each medical institution within the preset service time, and determining the reachable node area and the unreachable node area; reallocating the supply capacity of each medical institution, and calculating the actual supply-demand ratio of each medical institution; respectively calculating the weighted sum of the actual supply-demand ratios of all medical institutions in the reachable node area of ​​the Thiessen polygon, and obtaining the accessibility distribution in the study area. The present invention measures the accessibility of urban medical services under the scenario of heavy rain and waterlogging from a global perspective, which is more in line with the actual situation of medical accessibility analysis.

Description

Technical Field

[0001] The present invention belongs to the technical field of urban planning, and in particular relates to a medical accessibility analysis method and system for urban waterlogging emergencies. Background Art

[0002] In a rainstorm environment, urban roads may be interrupted or paralyzed due to waterlogging and collapse, which may cause emergency vehicles to detour, slow down, or even stagnate, thereby prolonging the medical rescue response time. Medical accessibility refers to the degree to which people can obtain necessary medical services. It is an important indicator for measuring the effectiveness of the medical system. Good medical accessibility can ensure timely, fair and high-quality medical services. The analysis of medical accessibility for urban waterlogging can promote the optimization of the medical institution system to cope with the medical rescue problems of emergencies under heavy rains, and achieve comprehensive medical security by optimizing the spatial pattern of medical services.

[0003] Existing urban medical accessibility analysis methods often select administrative units or residential communities as research units, which makes it difficult to accurately simulate the actual medical rescue path and the coverage is not comprehensive enough. Moreover, they only focus on the medical needs within the service area and ignore the peripheral medical needs, which is contrary to the actual medical rescue situation. In addition, existing urban medical accessibility analysis often selects travel distance as the transportation cost, which cannot reflect the medical characteristics of urban waterlogging emergencies and is even more difficult to accurately describe the actual situation of accessibility.

[0004] Therefore, a new medical accessibility analysis method is needed to measure the accessibility of urban medical services under heavy rain and waterlogging scenarios from a global perspective. Summary of the invention

[0005] In view of this, the present invention proposes a medical accessibility analysis method and system for urban waterlogging emergencies, which are used to solve the problem that the existing medical accessibility analysis method cannot measure the accessibility of urban medical services in rainstorm waterlogging scenarios from a global perspective.

[0006] In a first aspect, the present invention discloses a medical accessibility analysis method for urban waterlogging emergencies, the method comprising:

[0007] Obtain road network data and waterlogged road damage data in the study area to build a transportation network;

[0008] Generating Thiessen polygons with the nodes of the transportation network as the center, calculating the total population and the supply capacity of medical institutions within the Thiessen polygons, and coupling the total population and the supply capacity of medical institutions with the nodes of the transportation network;

[0009] Based on the Dijkstra algorithm, the reachable node set of each medical institution within the preset service time is calculated to determine the reachable node area and the unreachable node area;

[0010] Redistribute the supply capacity of each medical institution according to the medical needs of the unreachable node area;

[0011] Calculate the actual supply-demand ratio of each medical institution according to the supply capacity of each medical institution after the redistribution and the total population within the Thiessen polygon;

[0012] The weighted sum of the actual supply-demand ratios of all medical institutions in the reachable node area of ​​the Thiessen polygon is calculated respectively to obtain the accessibility distribution in the study area.

[0013] On the basis of the above technical solution, preferably, the construction of the transportation network specifically includes:

[0014] Extract road network nodes, edges, section lengths, and section design speeds through road network data;

[0015] Calculate the travel speed and travel time of the damaged road section through the damaged road section damage data; the damaged road section damage data includes the type and degree of damage of the damaged road section; the damaged road section damage types include waterlogging, landslide and coexistence of waterlogging and landslide;

[0016] A transportation network is constructed by taking road network nodes as nodes of the transportation network, edges formed by adjacent road network nodes as edges of the transportation network, and road section length, road section design speed, and road section travel speed and road section travel time as attribute information of each edge of the transportation network.

[0017] On the basis of the above technical solution, preferably, the calculation of the travel speed and travel time of the damaged road section by using the damaged data of the waterlogged road section specifically includes:

[0018] The formula for calculating the speed of a road section under flooding is:

[0019]

[0020] Among them, i, j are node numbers, i, j = 1, 2, ..., N, N is the total number of nodes in the transportation network, is the speed of the road section under flooding conditions, v ij is the design speed of the road section, f ij is the depth of water accumulation on the road section, a is the critical water depth at which the vehicle is forced to stop, b is the attenuation index, and tanh is the hyperbolic tangent function;

[0021] The formula for calculating the speed of the road section under landslide is:

[0022]

[0023] u(S,H,D)=0.01S+0.049H+0.803f(D)

[0024] in, is the speed under landslide condition, u(S,H,D) is the damage condition assessment value, S is the road damage area, H is the road damage depth, D is the lane net width, and f(D) is the lane net width factor adjustment function;

[0025] The formula for calculating the speed of a road section where waterlogging and landslides coexist is:

[0026]

[0027] in, It is the traffic speed of the road section when waterlogging and collapse coexist;

[0028] Calculate the travel time of a road section, specifically:

[0029]

[0030] in, for or Represents the speed of the damaged road section, t ij is the road section travel time, l ij is the length of the road segment.

[0031] On the basis of the above technical solution, preferably, the calculating the total population and the supply capacity of medical institutions within the Thiessen polygon, and coupling the total population and the supply capacity of medical institutions with the nodes of the transportation network specifically include:

[0032] Count the total population within the Thiessen polygon and assign the total population to the closest node;

[0033] Multiply the number of beds in each medical institution by the grade coefficient of each medical institution to calculate the supply capacity of each medical institution;

[0034] The locations of various medical institutions are spatially matched with the transportation network, and the locations of the medical institutions and the supply capabilities of the medical institutions are mapped to the closest nodes.

[0035] On the basis of the above technical solution, preferably, the reallocation of the supply capacity of each medical institution according to the medical demand of the unreachable node area specifically includes:

[0036] Taking the travel time of the road section as the weight, the Dijkstra algorithm is used to calculate the nearest medical institution in each unreachable node area, and the adjacent unreachable node set of each medical institution is obtained;

[0037] The redistribution coefficient of the supply capacity of each medical institution is calculated according to the total population of the adjacent unreachable node set, and the formula is:

[0038]

[0039] Among them, λ p is the redistribution coefficient of the supply capacity of the pth medical institution, S outp is the set of adjacent unreachable nodes of the p-th medical institution, is the kth node d k The total population, is the total population of all nearby unreachable nodes of the pth medical institution, S p is the reachable node set of the pth medical institution, is the total population of the node reachable by the pth medical institution; p=1,2,…,m, m is the total number of medical institutions; k=1,2,…,N, N is the total number of nodes in the transportation network;

[0040] Redistribute the supply capacity of each medical institution according to the redistribution coefficient:

[0041]

[0042] M p , Provide capacity for the pth medical institution before and after redistribution.

[0043] On the basis of the above technical solution, preferably, the actual supply-demand ratio of each medical institution is calculated according to the supply capacity of each medical institution after the reallocation and the total population within the Thiessen polygon, specifically including:

[0044] The Huff model is used to calculate the probability of each medical institution being selected. The formula is:

[0045]

[0046] Among them, α ip is the selection weight of the ith node for the pth medical institution, t mini,p is the shortest travel time between the ith node and the pth medical institution, t mini,k is the shortest travel time between the i-th and k-th nodes, t0 is the preset service time; f(·) is the time decay function; i=1,2,…,N, N is the total number of nodes in the transportation network;

[0047] The actual supply-demand ratio is calculated based on the supply capacity of each medical institution after redistribution. The formula is:

[0048]

[0049] Among them, R p is the actual supply-demand ratio of the pth medical institution, S p is the area of ​​the reachable node of the pth medical institution.

[0050] On the basis of the above technical solution, preferably, the formula for the accessibility distribution in the study area is:

[0051]

[0052] Among them, A i is the reachability of the Thiessen polygon where the i-th node is located, S i is the area of ​​the Thiessen polygon where the i-th node is located.

[0053] In a first aspect, the present invention discloses a medical accessibility analysis system for urban waterlogging emergencies, the system comprising:

[0054] Network building module: obtain the road network data and waterlogged road damage data of the study area and build a transportation network;

[0055] Data coupling module: used for generating Thiessen polygons with the nodes of the transportation network as the center, calculating the total population and the supply capacity of medical institutions within the Thiessen polygons, and coupling the total population and the supply capacity of medical institutions with the nodes of the transportation network;

[0056] Area division module: used to calculate the reachable node set of each medical institution within the preset service time based on the Dijkstra algorithm, and determine the reachable node area and the unreachable node area;

[0057] Supply and demand calculation module: used to reallocate the supply capacity of each medical institution according to the medical demand of the unreachable node area; calculate the actual supply and demand ratio of each medical institution according to the reallocated supply capacity of each medical institution and the total population within the Thiessen polygon;

[0058] Accessibility calculation module: used to calculate the weighted sum of the actual supply-demand ratios of all medical institutions in the reachable node area of ​​the Thiessen polygon, and obtain the accessibility distribution in the study area.

[0059] In a third aspect of the present invention, an electronic device is disclosed, comprising: at least one processor, at least one memory, a communication interface and a bus;

[0060] Wherein, the processor, memory, and communication interface communicate with each other via the bus;

[0061] The memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to implement the method according to the first aspect of the present invention.

[0062] According to a fourth aspect of the present invention, a computer-readable storage medium is disclosed, wherein the computer-readable storage medium stores computer instructions, and the computer instructions enable a computer to implement the method described in the first aspect of the present invention.

[0063] Compared with the prior art, the present invention has the following beneficial effects:

[0064] 1) The present invention uses the Thiessen polygon constructed with the nodes of the transportation network as the research unit, and takes the nodes of the transportation network as the demand points, couples the road topology network, population distribution and the scale of medical institutions, and comprehensively considers the medical needs of inaccessible areas, globally redistributes the supply capacity of medical institutions, and conducts accessibility analysis, which can more accurately reflect the distribution of medical accessibility of urban waterlogging emergencies and is more in line with the actual situation of medical accessibility.

[0065] 2) The present invention calculates the road section travel speed and travel time under three damage states, namely, waterlogging, landslide, and coexistence of waterlogging and landslide, through the damaged data of waterlogged road sections, and uses the road section travel time as the weight for selecting the shortest path, which is more in line with the actual needs of medical rescue scenarios in heavy rains, dynamically reflects the delay in medical response time, and improves the timeliness of medical rescue.

[0066] 3) The present invention calculates the redistribution coefficient of the supply capacity of each medical institution according to the total population of the set of adjacent unreachable nodes, redistributes the supply capacity of each medical institution according to the redistribution coefficient, and then calculates the probability of each medical institution being selected and calculates the actual supply-demand ratio. It can consider medical needs from a global perspective, conduct a balanced assessment of the supply and demand of medical resources, and improve the accuracy of accessibility distribution in the study area.

[0067] 4) The present invention measures the accessibility of urban medical services under the scenario of heavy rain and urban flooding from a global perspective. At a time when extreme heavy rains and urban flooding are frequent, the research results have guiding significance for the site selection and scale adjustment of medical institutions, and can provide a scientific basis for improving urban medical service capabilities and optimizing medical rescue travel plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0069] Figure 1 It is a flow chart of the medical accessibility analysis method for urban waterlogging emergencies of the present invention;

[0070] Figure 2 It is a framework diagram of the medical accessibility analysis method for urban waterlogging emergencies of the present invention;

[0071] Figure 3 This is a schematic diagram of the path between the demand point and the medical institution in case of heavy rain;

[0072] Figure 4 Schematic diagram of supply capacity reallocation to healthcare institutions. DETAILED DESCRIPTION

[0073] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0074] The present invention mainly solves the following technical problems:

[0075] (1) Most existing studies use administrative units or residential areas as research units. However, administrative units are usually divided into large areas, and different areas of the same administrative unit may have large differences in actual travel, making accessibility analysis inaccurate. Taking residential areas as research units does not take into account the medical rescue needs outside residential areas, which is not comprehensive enough. Therefore, the present invention selects the Thiessen polygon generated with the nodes of the traffic network in the study area as the center as the research unit, and calculates the accessibility of each node as the demand point, which better fits the actual medical rescue scenario and makes the determination of the shortest path more realistic.

[0076] (2) Existing accessibility analysis methods often ignore the medical needs of areas outside the service scope that are considered inaccessible. However, in actual rescue work, if there is a need in areas that are far away or take a long time, nearby medical institutions are still needed to provide rescue. Therefore, the present invention comprehensively considers the medical needs of inaccessible areas, reallocates medical resources, and then conducts accessibility analysis so that it can accurately reflect the actual accessibility situation, which has guiding significance for the site selection and scale adjustment of medical institutions.

[0077] (3) Existing accessibility models often use distance as the selection weight of the shortest path, which is not suitable for rainstorm medical rescue scenarios. Medical rescue needs to have a strong timeliness. Therefore, the present invention selects the shortest travel time as the road resistance parameter to make it better fit the real scene and dynamically reflect the delay of medical response time.

[0078] See also Figure 1 , Figure 2 The present invention discloses a medical accessibility analysis method for urban waterlogging emergencies, the method comprising:

[0079] S1. Obtain the road network data and waterlogged road damage data of the study area and construct a transportation network.

[0080] The present invention constructs a traffic network based on road network data and coupled with waterlogged road section damage data under heavy rain conditions.

[0081] Step S1 specifically includes the following sub-steps:

[0082] S11. Extract road network nodes, edges, section lengths, and section design speeds through road network data.

[0083] The road network data includes the road topology and basic attribute information. The road topology includes road network nodes and edges. The i-th road network node is represented by d i , the total number of nodes is N, where the edge formed by adjacent network nodes i and j is represented by e ij ,The basic attribute information includes the road section length and the road section design speed corresponding to each edge.

[0084] S12. Calculate the travel speed and travel time of the damaged road section based on the damaged data of the waterlogged road section.

[0085] In an embodiment of the present invention, the waterlogged road section damage data includes the type and degree of waterlogged road section damage; wherein the waterlogged road section damage types include three common road obstruction types in heavy rain scenarios: waterlogging, landslides, and waterlogging and landslides coexisting. Therefore, the speed and travel time of the damaged road section include the speed and travel time of the road section in the waterlogged state, the speed and travel time of the road section in the landslide state, and the speed and travel time of the road section in the waterlogged and landslides coexisting state.

[0086] S121. Calculate the speed of the road section under waterlogging conditions. The formula is:

[0087]

[0088] Among them, i, j are node numbers, i, j = 1, 2, ..., N, N is the total number of nodes in the transportation network, is the speed of the road section under flooding conditions, v ij is the design speed of the road section, f ij is the depth of water accumulation on the road section, a is the critical water depth at which the vehicle is forced to stop, b is the attenuation index, and tanh is the hyperbolic tangent function;

[0089] S122. Calculate the speed of the road section under the landslide condition. The formula is:

[0090]

[0091] u(S,H,D)=0.01S+0.049H+0.803f(D)

[0092] in, is the speed under landslide condition, u(S,H,D) is the damage condition assessment value, S is the road damage area, H is the road damage depth, D is the lane net width, and f(D) is the lane net width factor adjustment function;

[0093] S123. Calculate the speed of the road section where waterlogging and landslides coexist. The formula is:

[0094]

[0095] in, It is the traffic speed of the road section when waterlogging and collapse coexist;

[0096] S124. Calculate the road section travel time using the formula:

[0097]

[0098] in, for or Represents the speed of the damaged road section, t ij is the road section travel time, l ij is the length of the road segment.

[0099] S13. Build a transportation network.

[0100] The present invention constructs a traffic network by adding the speed and travel time of damaged road sections to the basic attribute information on the basis of the road network data. That is, the traffic network is constructed by taking the road network nodes as nodes of the traffic network, the edges formed by adjacent road network nodes as edges of the traffic network, and the road section length, the road section design speed, and the speed and travel time of damaged road sections as the attribute information of each edge of the traffic network.

[0101] S2. Generate Thiessen polygons with the nodes of the transportation network as the center, calculate the total population and the supply capacity of medical institutions within the Thiessen polygons, and couple the total population and the supply capacity of medical institutions with the nodes of the transportation network.

[0102] Based on the transportation network, the present invention couples population data and the supply capacity of medical institutions to achieve multi-source data fusion, which facilitates the subsequent calculation of the shortest path and travel time.

[0103] Specifically, Thiessen polygons are generated with the nodes of the transportation network as the center, the total population within the Thiessen polygons is counted, and the total population is distributed to the closest node, that is, the center of the Thiessen polygon, to facilitate subsequent shortest path and travel time calculations.

[0104] The supply capacity of each medical institution is calculated by multiplying the number of beds of each medical institution by the grade coefficient of each medical institution. The formula is:

[0105] M p =NHB p *GH p

[0106] Among them, M p is the supply capacity of the pth medical institution, NHB p is the number of beds in the pth medical institution, GH p is the grade coefficient of the pth medical institution.

[0107] The locations of various medical institutions are spatially matched with the transportation network, and the locations and supply capacities of the medical institutions are mapped to the nearest nodes to facilitate subsequent calculations of the shortest path and travel time.

[0108] S3. Based on the Dijkstra algorithm, the reachable node set of each medical institution within the preset service time is calculated to determine the reachable node area and the unreachable node area.

[0109] Medical rescue has a higher requirement for timeliness than other travel purposes, and waterlogging or landslides have an impact on speed and traffic restrictions on traffic route selection, such as Figure 3 The figure shows a schematic diagram of the path between the demand point and the medical institution under heavy rain conditions. It can be seen that it may take longer to select a route by distance. Therefore, the present invention uses the travel time rather than the distance as the weight of the shortest route, that is, the travel time of the road section as the weight, and generates the node set that each medical institution can reach within the preset service time and the shortest travel time set with which it has a mapping relationship based on the Dijkstra algorithm to divide the service range.

[0110] Step S3 specifically includes the following sub-steps:

[0111] S31, let the medical institution set P = {m p}, p = 1, 2, ..., m, m is the total number of medical institutions in the study area, and the road traffic node set D in the study area is {d i}, i = 1, 2, ..., N, N is the total number of nodes in the study area, and the reachable node set of each medical institution

[0112] S32. Select any medical institution m from the set P.p As the starting node of the path, traverse all nodes in set D as the ending node of the path, use the travel time of the section as the weight, and use the Dijkstra algorithm to obtain node d i 、m p The shortest travel time between mini,p , assuming that the preset service time is t0, and the distance corresponding to the travel time t0 is used as the service radius of each medical institution. mini,p If it is less than t0, the road network node d i Add the reachable node set S p In the above example, let the set S p There are q nodes in total, then:

[0113] S p =*d1,d2,……,d q +

[0114] And generate a one-to-one mapping of the shortest travel time set:

[0115] t i,p =*t min1,p ,t min2,p ,……,t minq,p +

[0116] Among them, t mini,p For node m p d i The shortest travel time between, t0 is the service radius;

[0117] S33, repeat step S32 until all nodes in the medical institution set M are traversed, and the iteration ends;

[0118] Thus, we can obtain the reachable node set of each medical institution and S1~S p , and the shortest travel time set t that has a mapping relationship with it i,1 ~t i,p :

[0119]

[0120] Calculate the unreachable node set as follows:

[0121] D out =D-(S1∪S2∪……∪S p )

[0122] Among them, D out is the set of unreachable nodes, D is the set of nodes in the transportation network, S1~S p is the set of reachable nodes of each medical institution.

[0123] According to the above reachable node set and unreachable node set, the reachable node area and the unreachable node area can be determined. The present invention combines the specific scene of rainstorm waterlogging and selects the travel time as the characterization index, which is highly targeted and more suitable for urban waterlogging accessibility analysis under rainstorm scenes.

[0124] S4. Reallocate the supply capacity of each medical institution according to the medical needs of the unreachable node area.

[0125] Step S4 specifically includes the following sub-steps:

[0126] S41. Using the road section travel time as the weight, the Dijkstra algorithm is used to calculate the nearest medical institution in each unreachable node area, and the adjacent unreachable node set of each medical institution is obtained.

[0127] Suppose each medical institution is close to a set of unreachable nodes Unreachable node set D out =*d r +, r = 1, 2, …, u, u is the total number of unreachable nodes.

[0128] From the set D out Select any node as the path starting node, traverse all medical institutions in the medical institution set P as the path ending node, and use the Dijkstra algorithm to obtain node d r The nearest medical institution m p , and change node d r Add the adjacent unreachable node set S of the corresponding medical institution outp middle:

[0129] S outp =*d1,d2,……,d r +

[0130] S42, repeat step S41 until the unreachable area node set D is traversed out All nodes in the iteration are completed, and the adjacent unreachable node set S of each medical institution is obtained. out1 ~S outp :

[0131]

[0132] S43. Calculate the redistribution coefficient of the supply capacity of each medical institution according to the total population of the set of adjacent unreachable nodes.

[0133] The formula for calculating the redistribution coefficient is:

[0134]

[0135] Among them, λ pis the redistribution coefficient of the supply capacity of the pth medical institution, S outp is the set of adjacent unreachable nodes of the p-th medical institution, is the kth node d k The total population, is the total population of all nearby unreachable nodes of the pth medical institution, S p is the reachable node set of the pth medical institution, is the total population of the node reachable by the pth medical institution; p=1,2,…,m, m is the total number of medical institutions; k=1,2,…,N, N is the total number of nodes in the transportation network;

[0136] S44, reallocating the supply capacity of each medical institution according to the reallocation coefficient:

[0137]

[0138] M p , Provide capacity for the pth medical institution before and after redistribution.

[0139] Figure 4 This is a schematic diagram of the redistribution of the supply capacity of medical institutions, where hospitals represent medical institutions. Since medical rescue is fair, the medical needs of remote areas also need to be met. Compared with the traditional accessibility calculation method, the present invention comprehensively considers the medical needs of inaccessible areas to calculate the supply capacity of medical institutions and redistributes the supply capacity of medical institutions. This can more accurately reflect the distribution of medical accessibility in urban waterlogging emergencies and is more in line with the actual situation of medical accessibility.

[0140] S5. Calculate the actual supply-demand ratio of each medical institution based on the supply capacity of each medical institution after the reallocation and the total population within the Thiessen polygon.

[0141] Step S5 specifically includes the following sub-steps:

[0142] S51. Use the Huff model to calculate the probability of each medical institution being selected.

[0143] In actual situations, accessibility will gradually decay as travel time increases. Therefore, the present invention considers the rescue attenuation effect and adds an additional time decay function within the service radius of the medical institution. The formula is:

[0144]

[0145] Among them, f(t mini,p ) is the Gaussian decay function based on travel time, and t0 is the preset service time.

[0146] When a node area is considered reachable by multiple medical institutions, it is necessary to determine the probability of its selection by calculating the supply capacity ratio of each medical institution. The formula for calculating the probability of each medical institution being selected is:

[0147]

[0148] Among them, α ip is the selection weight of the ith node for the pth medical institution, t mini,p is the shortest travel time between the i-th and p-th nodes, t mini,k is the shortest travel time between the i-th and k-th nodes, t0 is the preset service time; f(·) is the time decay function; i=1,2,…,N, N is the total number of nodes in the transportation network;

[0149] S52. Calculate the actual supply-demand ratio based on the supply capacity of each medical institution after redistribution.

[0150] The actual supply-demand ratio is the ratio of the supply capacity of the redistributed medical institution to the medical demand of all node areas within its reach, and the formula is:

[0151]

[0152] Among them, R p is the actual supply-demand ratio of the pth medical institution, S p is the area of ​​the reachable node of the pth medical institution.

[0153] S6. Calculate the weighted sum of the actual supply-demand ratios of all medical institutions in the reachable node area of ​​the Thiessen polygon respectively to obtain the accessibility distribution in the study area.

[0154] According to the rescue attenuation effect, the probability of being selected and the actual supply-demand ratio, the supply-demand ratio of each demand unit, that is, the sum of the supply-demand ratios of all medical institutions within the service range of the Thiessen polygon centered on the road network node, is calculated to obtain the accessibility distribution in the study area. The formula for the accessibility distribution in the study area is:

[0155]

[0156] Among them, A i is the reachability of the Thiessen polygon where the i-th node is located, S i is the area of ​​the Thiessen polygon where the i-th node is located.

[0157] This paper selects Thiessen polygons centered on traffic network nodes as the research unit, couples the road topology network, population distribution and the scale of medical institutions, uses population distribution and the scale of medical institutions to characterize the demand scale and supply capacity, takes travel time as the transportation cost based on the timeliness of medical rescue, and comprehensively considers the occupation of medical resources in inaccessible areas, and measures the accessibility of urban medical services under the scenario of heavy rain and waterlogging from a global perspective. At a time when extreme heavy rains are frequent and urban waterlogging is frequent, the research results can provide a scientific basis for improving urban medical supply capacity and optimizing medical rescue travel plans.

[0158] Corresponding to the above method embodiment, the present invention also proposes a medical accessibility analysis system for urban waterlogging emergencies, the system comprising:

[0159] Network building module: obtain the road network data and waterlogged road damage data of the study area and build a transportation network;

[0160] Data coupling module: used for generating Thiessen polygons with the nodes of the transportation network as the center, calculating the total population and the supply capacity of medical institutions within the Thiessen polygons, and coupling the total population and the supply capacity of medical institutions with the nodes of the transportation network;

[0161] Area division module: used to calculate the reachable node set of each medical institution within the preset service time based on the Dijkstra algorithm, and determine the reachable node area and the unreachable node area;

[0162] Supply and demand calculation module: used to reallocate the supply capacity of each medical institution according to the medical demand of the unreachable node area; calculate the actual supply and demand ratio of each medical institution according to the reallocated supply capacity of each medical institution and the total population within the Thiessen polygon;

[0163] Accessibility calculation module: used to calculate the weighted sum of the actual supply-demand ratios of all medical institutions in the reachable node area of ​​the Thiessen polygon, and obtain the accessibility distribution in the study area.

[0164] The above system embodiments and method embodiments correspond one to one, and for a brief description of the system embodiments, please refer to the method embodiments.

[0165] The present invention also discloses an electronic device, comprising: at least one processor, at least one memory, a communication interface and a bus; wherein the processor, memory, and communication interface communicate with each other through the bus; the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to implement the aforementioned method of the present invention.

[0166] The present invention also discloses a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, wherein the computer instructions enable the computer to implement all or part of the steps of the method described in the embodiment of the present invention. The storage medium includes: a USB flash drive, a mobile hard disk, a read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk, and other media that can store program codes.

[0167] The system embodiment described above is merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be distributed to multiple network units. A person skilled in the art may select some or all of the modules according to actual needs to achieve the purpose of the solution of this embodiment without creative effort.

[0168] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A medical accessibility analysis method for urban waterlogging emergencies, characterized in that: The method comprises: Obtain road network data and waterlogged road damage data in the study area to build a transportation network; Generating Thiessen polygons with the nodes of the transportation network as the center, calculating the total population and the supply capacity of medical institutions within the Thiessen polygons, and coupling the total population and the supply capacity of medical institutions with the nodes of the transportation network; Based on the Dijkstra algorithm, the reachable node set of each medical institution within the preset service time is calculated to determine the reachable node area and the unreachable node area; Redistribute the supply capacity of each medical institution according to the medical needs of the unreachable node area; Calculate the actual supply-demand ratio of each medical institution according to the supply capacity of each medical institution after the redistribution and the total population within the Thiessen polygon; Calculate the weighted sum of the actual supply-demand ratios of all medical institutions in the reachable node area of ​​the Thiessen polygon respectively to obtain the accessibility distribution in the study area; The calculating the total population and the supply capacity of medical institutions within the Thiessen polygon and coupling the total population and the supply capacity of medical institutions with the nodes of the transportation network specifically includes: Count the total population within the Thiessen polygon and assign the total population to the closest node; Multiply the number of beds in each medical institution by the grade coefficient of each medical institution to calculate the supply capacity of each medical institution; Spatially matching the locations of various medical institutions with the transportation network, and mapping the locations of the medical institutions and the supply capacity of the medical institutions to the closest nodes; The reallocation of the supply capacity of each medical institution according to the medical demand of the unreachable node area specifically includes: Taking the travel time of the road section as the weight, the Dijkstra algorithm is used to calculate the nearest medical institution in each unreachable node area, and the adjacent unreachable node set of each medical institution is obtained; The redistribution coefficient of the supply capacity of each medical institution is calculated according to the total population of the adjacent unreachable node set, and the formula is: Among them, λ p is the redistribution coefficient of the supply capacity of the pth medical institution, S 0utp is the set of adjacent unreachable nodes of the p-th medical institution, is the kth node d k The total population, is the total population of all nearby unreachable nodes of the pth medical institution, S p is the reachable node set of the pth medical institution, is the total population of the node reachable by the pth medical institution; p=1,2,…,m, m is the total number of medical institutions; k=1,2,…,N, N is the total number of nodes in the transportation network; Redistribute the supply capacity of each medical institution according to the redistribution coefficient: M p , Provide capacity for the pth medical institution before and after redistribution.

2. The medical accessibility analysis method for urban waterlogging emergencies according to claim 1 is characterized in that: The construction of the transportation network specifically includes: Extract road network nodes, edges, section lengths, and section design speeds through road network data; Calculate the travel speed and travel time of the damaged road section through the damaged road section damage data; the damaged road section damage data includes the type and degree of damage of the damaged road section; the damaged road section damage types include waterlogging, landslide and coexistence of waterlogging and landslide; A transportation network is constructed by taking road network nodes as nodes of the transportation network, edges formed by adjacent road network nodes as edges of the transportation network, and road section length, road section design speed, and road section travel speed and road section travel time as attribute information of each edge of the transportation network.

3. The medical accessibility analysis method for urban waterlogging emergencies according to claim 2 is characterized in that: The calculation of the travel speed and travel time of the damaged road section by using the damaged data of the waterlogged road section specifically includes: The formula for calculating the speed of a road section under flooding is: Among them, i, j are node numbers, i, j = 1, 2, ..., N, N is the total number of nodes in the transportation network, is the speed of the road section under flooding conditions, v ij is the design speed of the road section, f ij is the depth of water accumulation on the road section, a is the critical water depth at which the vehicle is forced to stop, b is the attenuation index, and tanh is the hyperbolic tangent function; The formula for calculating the speed of the road section under landslide is: u(S,H,D)=0.01S+0.049H+0.803f(D) in, is the speed under landslide condition, u(S,H,D) is the damage condition assessment value, S is the road damage area, H is the road damage depth, D is the lane net width, and f(D) is the lane net width factor adjustment function; The formula for calculating the speed of a road section where waterlogging and landslides coexist is: in, It is the traffic speed of the road section when waterlogging and collapse coexist; Calculate the travel time of a road section, specifically: in, for or Represents the speed of the damaged road section, t ij is the road section travel time, l ij is the length of the road segment.

4. The medical accessibility analysis method for urban waterlogging emergencies according to claim 1 is characterized in that: The calculation of the actual supply-demand ratio of each medical institution according to the supply capacity of each medical institution after the redistribution and the total population within the Thiessen polygon specifically includes: The Huff model is used to calculate the probability of each medical institution being selected. The formula is: Among them, α ip is the selection weight of the ith node for the pth medical institution, t mini,p is the shortest travel time between the ith node and the pth medical institution, t mini,k is the shortest travel time between the i-th and k-th nodes, t0 is the preset service time; f(·) is the time decay function; i=1,2,…,N, N is the total number of nodes in the transportation network; The actual supply-demand ratio is calculated based on the supply capacity of each medical institution after redistribution. The formula is: Among them, R p is the actual supply-demand ratio of the pth medical institution, S p is the area of ​​the reachable node of the pth medical institution.

5. The medical accessibility analysis method for urban waterlogging emergencies according to claim 4 is characterized in that: The formula for accessibility distribution within the study area is: Among them, A i is the reachability of the Thiessen polygon where the i-th node is located, S i is the area of ​​the Thiessen polygon where the i-th node is located.

6. A medical accessibility analysis system for urban waterlogging emergencies, characterized in that: The system comprises: Network building module: obtain the road network data and waterlogged road damage data of the study area to build a transportation network; Data coupling module: used to generate Thiessen polygons with the nodes of the transportation network as the center, calculate the total population and the supply capacity of medical institutions within the Thiessen polygons, and couple the total population and the supply capacity of medical institutions with the nodes of the transportation network; the calculation of the total population and the supply capacity of medical institutions within the Thiessen polygons, and coupling the total population and the supply capacity of medical institutions with the nodes of the transportation network specifically include: Count the total population within the Thiessen polygon and assign the total population to the closest node; Multiply the number of beds in each medical institution by the grade coefficient of each medical institution to calculate the supply capacity of each medical institution; Spatially matching the locations of various medical institutions with the transportation network, and mapping the locations of the medical institutions and the supply capacity of the medical institutions to the closest nodes; Area division module: used to calculate the reachable node set of each medical institution within the preset service time based on the Dijkstra algorithm, and determine the reachable node area and the unreachable node area; Supply and demand calculation module: used to reallocate the supply capacity of each medical institution according to the medical demand of the unreachable node area; calculate the actual supply and demand ratio of each medical institution according to the reallocated supply capacity of each medical institution and the total population within the Thiessen polygon; the reallocation of the supply capacity of each medical institution according to the medical demand of the unreachable node area specifically includes: Taking the travel time of the road section as the weight, the Dijkstra algorithm is used to calculate the nearest medical institution in each unreachable node area, and the adjacent unreachable node set of each medical institution is obtained; The redistribution coefficient of the supply capacity of each medical institution is calculated according to the total population of the adjacent unreachable node set, and the formula is: Among them, λ p is the redistribution coefficient of the supply capacity of the pth medical institution, S outp is the set of adjacent unreachable nodes of the p-th medical institution, is the kth node d k The total population, is the total population of all nearby unreachable nodes of the pth medical institution, S p is the reachable node set of the pth medical institution, is the total population of the node reachable by the pth medical institution; p=1,2,…,m, m is the total number of medical institutions; k=1,2,…,N, N is the total number of nodes in the transportation network; Redistribute the supply capacity of each medical institution according to the redistribution coefficient: M p , Supply capacity for the pth medical institution before and after redistribution; Accessibility calculation module: used to calculate the weighted sum of the actual supply-demand ratios of all medical institutions in the reachable node area of ​​the Thiessen polygon, and obtain the accessibility distribution in the study area.

7. An electronic device, characterized in that: include: at least one processor, at least one memory, a communication interface, and a bus; Wherein, the processor, memory, and communication interface communicate with each other via the bus; The memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to implement the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions enable a computer to implement the method according to any one of claims 1 to 5.

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