Infectious disease epidemiology under meteorological factors: A review of mathematical models and an extended SEIR framework

Historical records of childhood disease incidence reveal complex dynamics. For measles, a simple model has indicated that epidemic patterns represent attractors of a nonlinear dynamic system and that transitions between different attractors are driven by slow changes in birth rates and vaccination levels. The same analysis can explain the main features of chickenpox dynamics, but fails for rubella and whooping cough. We show that an additional (perturbative) analysis of the model, together with knowledge of the population size in question, can account for all the observed incidence patterns by predicting how stochastically sustained transient dynamics should be manifested in these systems.

Regional scale spatio-temporal variability of soil moisture and its relationship with meteorological factors over the Korean peninsula

PDF HTML阅读 XML下载 导出引用 引用提醒 昼间气象条件对城市道路绿化带空气净化效果的影响——以太原市为例 DOI: 10.5846/stxb201304210761 作者: 作者单位: 山西农业大学农学院,山西农业大学,山西农业大学,山西农业大学,山西农业大学,山西农业大学,山西农业大学 作者简介: 通讯作者: 中图分类号: TU985.18;X51 基金项目: 国家自然科学基金资助项目(30870434) Effects of meteorological factors on air purification by green belts along urban roads in the daytime: a case study in Taiyuan Author: Affiliation: Shanxi Agricultural University,Shanxi Agricultural University,Taigu China,Shanxi Agricultural University,Taigu China,Shanxi Agricultural University,Taigu China,Shanxi Agricultural University,Taigu China,Shanxi Agricultural University,Taigu China,Shanxi Agricultural University,Taigu China Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:道路绿化带可以净化空气,改善道路环境,道路中的小气候条件会改变道路污染物扩散方式和速度,进而会影响到绿化带对污染物净化效果。气象条件对道路绿地对大气污染物净化效果影响的研究将有助于了解道路绿地的净化途径,为改善城市道路环境提供依据。对太原市18个道路绿地气象因子和5种主要污染物浓度进行了观测。结果表明:夏季,太原市城市道路内各气象要素之间存在一定的相关性,气温和地温正相关显著,空气相对湿度与地温及气温呈显著和极显著负相关。大部分情况下,有绿地非机动车道污染物平均浓度低于无绿地非机动车道对照点平均浓度,即道路绿地起到了对道路污染物的净化作用。道路绿地对污染物的净化百分率与气象因子存在显著的回归关系,并可以建立达到统计显著水平的回归方程,但不同污染物受不同的主导气象因子影响。 气象条件会影响道路绿地对道路污染物的净化效果,今后的城市建设和道路绿地规划中应更多地考虑气象条件对绿地净化效果的影响。 Abstract:Green belts along roads can purify the air and improve the air quality along the roads. The microclimate conditions around a road will affect the manner and speed of pollutant diffusion, and it may affect how effective the green belt is in removing pollutants from the air. In this study, the effects of microclimate conditions on the removal of pollutants by green belts along roads were monitored, and the results will provide a basis for improving the road environment by improving our understanding of the manner in which the air around roads is purified by green belts. Microclimate conditions (wind speed, air temperature, relative humidity in the air, surface temperature, and air pressure) and the concentrations of five major pollutants, SO2, NOx, NH3, total suspended particles (TSP) and respirable particulate matter (PM10), were observed along 18 roads with green belts in the city of Taiyuan. The meteorological elements correlated with each other along the Taiyuan roads in the summer. There were significant positive correlations between the wind speed and the surface temperature, and the air and surface temperatures also significantly positively correlated. However, the relative humidity, the surface temperature, and the air temperature were significantly negatively correlated. In most cases, the average pollutant concentration caused by non-motorized vehicles when a green belt was present was lower than the average pollutant concentration caused by non-motorized vehicles when a green belt was not present, so the green belt appeared to play a role in removing pollutants from the air around the road. The percentages of the concentrations of the five pollutants that were removed by the green belt had significant regression coefficients with the meteorological factors. Regression equations, and the statistical significances of the regressions, were established for the relationships between the pollutant removal percentages and the meteorological factors, but different pollutants were affected by different meteorological factors. The SO2 removal percentage was mostly affected by the wind speed and air temperature, the percentage removed increasing with both meteorological conditions. The NOx removal percentage was mainly affected by, and increased with, the ground temperature. The NH3 removal percentage was mainly influenced by, and increased with, the air temperature. The TSP removal percentage was mainly affected by, and increased with, the air humidity. The PM10 removal percentage was mainly affected by, and increased with, the air temperature and air pressure. Green space regulates, to a certain extent, the surrounding microclimate, and can cause the air temperature to decrease and the air humidity to increase in the summer. A decrease in air temperature around the road will decrease the rate of vertical diffusion of NOx, NH3, and PM10, but an increase in air humidity will promote a decrease in TSP concentrations around the road. In future ‘green’ road designs, an appropriate increase in the road green belt area will be beneficial in both improving the road microclimate environment and in decreasing the concentrations of solid contaminants (TSP) in the air. However, it will probably not be effective in improving the diffusion of NOx, NH3, and PM10. Weather conditions will affect the pollutant removal percentages achieved by green belts along roads, so more meteorological studies need to be conducted along road green belts to provide the information needed to improve our ability to achieve pollutant removal using green belts along roads in urban areas, and to improve road construction planning. 参考文献 相似文献 引证文献

Meteorological and demographic factors associated with the onset of acute appendicitis in rural islands of Japan

Meteorological factors and anthropogenic activities significantly affect atmospheric ammonia （NH3） concentration and its dry deposition. Former studies have examined the spatial and temporal variability in atmospheric NH3 concentrations at monthly scales. However, the characteristics of atmospheric concentrations at finer time scales such as hourly and daily scales and the influencing factors remain unclear. In this study, atmospheric NH3 concentration and related meteorological factors were continuously monitored online for one year in a double cropping rice region in subtropical China, and atmospheric NH3 concentration and its meteorological influencing factors as well as dry deposition were analyzed at different time scales （hourly, daily, and monthly）. The main results were as follows： The annual average daily concentration of NH3 in the rice area varied from 0.01 to 58.0 μg·m-3 （in N, same below）, and the annual average concentration was 5.3 μg·m-3. On the hourly scale, the 24-hour dynamics of atmospheric NH3 concentration showed a unimodal pattern, and the time of the NH3 peak appearance in different seasons was different； the time of the peak that appeared in winter lagged behind that in the other seasons. From the perspective of daily scale, NH3 concentration was mainly affected by fertilization in the paddy fields, peaking at 1-3 days after fertilization and then gradually decreasing. On the monthly scale, NH3 concentration peaked at 12.8 μg·m-3 in July and was the lowest in October at 1.6 μg·m-3. On the hourly scale, NH3 concentration varied seasonally due to the influences of meteorological factors, mainly as follows： NH3 concentration showed significant positive correlations with air temperature and solar radiation in all four seasons and with wind speed in spring and summer, whereas it showed significant negative correlations with relative humidity except in winter. On the daily scale, NH3 concentration showed a significant positive correlation with air temperature, rainfall, and solar radiation, whereas it showed a significant negative correlation with relative humidity. On the monthly scale, no significant correlation existed between each meteorological factor and NH3 concentration. The annual dry deposition flux （in N） calculated from the hourly average NH3 concentration was 8.5 kg·（hm2·a）-1, which was 11.6% higher than the annual flux calculated from the daily average and 12.4% higher than the annual flux calculated from the monthly average. In summary, there were significant daily and seasonal variations in atmospheric NH3 concentration in the paddy rice region in subtropical China, and conducting hourly-scale observations of NH3 concentration can help to reveal the multi-time scale variations in NH3 concentration and to quantify NH3 dry deposition more accurately.

Climate change, environmental factors, and COVID-19: Current evidence and urgent actions

To research regional difference of frost damage, meteorological observations were made at Hayakita, located in the south-east of the Ishikari-Yuhutsu plain in Hokkaido. Hayakita has crops that are the most easily damaged by frost in the plain. In particular paddy rice plants are damaged by the first frost when their growth is retarded by a cool summer. The first frost in Hayakita occurs 1 week earlier than in other parts of the plain. To research this problem, Chitose that has different topography from Hayakita, was selected as a control area and some meteorological factors such as air temperature, wind speed, solar radiation, net radiation and downward radiation were compared between Hayakita and Chitose. These areas are at the same altitude and share similar surface features. Although Hayakita is surrounded by hills, Chitose is in the center of the plain and is located 12 kilometers away from Hayakita.In this paper, the daily minimum air temperatures and 4-hour mean values of the meteorological factors in the springs and falls of 1983 and 1984 were compared between Hayakita and Chitose. Also the variations of these factors on clear nights were compared.Daily minimum air temperatures in both seasons were not significantly different between Hayakita and Chitose. This means that the advection and accumulation of air mass cooled on surrounding slopes are not significant as causes of the frost damage in Hayakita.The 4-hour mean value of wind speed at Chitose was always greater than that at Hayakita. However, there were no significant differences for the other factors, such as solar radiation, net radiation and downward radiation between Hayakita and Chitose. The air temperature in Hayakita was often lower than that in Chitose, especially in the lower range of temperatures. This tendency was more remarkable in fall than in spring. Sometimes the temperature difference between the two regions reached approximately 5K in fall, accompanied with a large difference of wind speed.This large difference of air temperature tended to be observed from 20:00 to 4:00 of clear nights. It was caused by temperatures in Chitose often being rapidly increased by raising wind speed during that time, but both temperature and wind speed in Hayakita remained low and unchanged. When comparing temperature profiles to 80 meters above ground level of both regions, it was noted that the stable layer formed by radiative cooling was destroyed from upper portion to near ground surface at Chitose, while, on the other hand, only the upper portion of the layer was destroyed at Hayakita. However, both stable layers remained during the nights when no temperature difference occurred between the regions. Therefore, the occurrence of temperature differences between the regions is due to the difference in the destruction ratio of the stable layer.The phenomena mentioned above, often appeared in the center of the plain when the upper wind (geostrophic wind) speed and/or direction changed. The upper wind data were obtained from radiosonde data at the 900mb isobaric surface above Sapporo. The changes of wind were classified by following two patterns: i) upper wind speed very small at first, becoming stronger later, and ii) upper wind direction changing from a direction in which WSR (Wind Speed Ratio: the ratio of surface wind speed to upper wind speed at a direction) is small to other one in which WSR is greater. Greater WSR means greater wind speed at ground level for a given upper wind speed; WSR is influenced by surrounding geographic features. Therefore, the WSR values at the center of the plain, lying between the high mountains to the east and west, were large for the north-south direction and small for the east-west direction. On the other hand, WSR values were relatively small for all directions in Hayakita. Thus wind speed in Hayakita was always smaller than that in the center of the plain.It can thus be recognized that low temperatures conti

The global outbreak of covid-19 pandemic is still affecting people around the globe very badly. Before the covid-19 pandemic outbreak, several research works were done for the detection and prevention of various infectious diseases using different mathematical modeling. Implementing mathematical modeling to resolve problems in Biology and physiology is generally called Mathematical Biology, an extremely interdisciplinary area. The applications of mathematical modeling in the analysis of infectious diseases help to concentrate on the necessary processes associated with forming the infectious disease epidemiology and specifications estimation. The compartmental mathematical model can be either SI, SIS, SIR, SIRS, or SEIR where S, I, R, and E denote susceptible, infected, recovered, and exposed respectively. Malaria is an infectious disease that has a large economic and health impact on society. This study aims to predict the estimation of suspected, infected and recovered people using the SIR mathematical model of the Barama area of Baksa District in Assam, India. Here we analyzed the Basic Reproductive Ratio of the SIR model for malaria disease and examined if malaria is epidemic or endemic in that area.

Modern infectious disease epidemiology makes heavy use of computational model–based approaches and a dynamical systems perspective. The importance of analyzing infectious diseases in such a way keeps increasing. However, infectious disease epidemiology is still often taught mainly from a medical and classical epidemiological study design (e.g., cohort, case-control) perspective. While textbooks and other resources that teach a model-based approach to infectious diseases exist, almost any such teaching material requires students to work with mathematical models and write computer code. This is a significant barrier for students who do not have a strong mathematical background or prior coding experience, which applies to many students in public health and related biomedical disciplines. It limits the number of students who can or want to engage with infectious disease epidemiology by using modern, systems modeling–based approaches. New tools and approaches are needed to reach a wider audience and allow students to learn concepts such as the reproductive number, herd immunity, critical community size, and the population-level impact of interventions from a dynamical systems and model perspective, without the obstacles of coding or having to formulate and analyze differential equations. Here, I describe a new software package for the widely used R language that allows individuals to explore and study concepts of infectious disease epidemiology by using a modern, dynamical systems model framework, without the need to read or write computer code. The package includes documentation and material to serve as a stand-alone tool—supplemented as needed with provided references—for students to get an introduction to important modern infectious disease concepts. The package is built in a modular way that allows a student to seamlessly continue on their journey of learning infectious disease modeling if they choose to do so. The different ways to use the package are described in detail, and examples are provided.

Unlocking pathogen genotyping information for public health by mathematical modeling

The association between meteorological parameters and viral transmission in temperate and subtropical arid climates is not fully understood. The climate in Qatar reaches extremes of heat and humidity but retains a similar pattern of transmission of respiratory viruses as in temperate climates. The need for a better understanding of the demographic and meteorological factors that drive the transmission of respiratory viruses in the community. To evaluate the relationship between meteorological and demographic factors on the transmission of 18 respiratory viruses in the State of Qatar. In total, 355,948 nasopharyngeal swabs were tested for respiratory viruses from 31-Dec-2018 to 29-Dec-2019. The study involved 18 viruses, of which only 8 viruses were included in the analysis: ADV, hBoV, Flu-A, Flu-B, hPIV3, hMPV, HRV, and RSV. Respiratory virus prevalence was compared with local meteorological data including outdoor air temperature; dew point; wind speed; atmospheric pressure; relative humidity; solar radiation, and demographic factors, including age, gender, and nationality. Transmission waves were seen for ADV, hBoV, Flu-A, Flu-B, hMPV, HRV and RSV but not with hPIV-3. Wind speed, air temperature, relative humidity, and solar radiation were significantly associated with Flu-A, Flu-B, hMPV, and RSV, which showed clear seasonality, but not with HRV, hBoV, and ADV, which had atypical seasonality and hPIV-3, which had no seasonality. Incidental associations could not be excluded and would need to be confirmed through multiple seasons. School age was the most significant demographic. Young children, rather than meteorological factors, served as the primary determinant of viral transmission. The proximity of 3 large viral waves to school reopening after the summer break suggested school transmission is an important contributor. The significant association of meteorological factors with viral transmission increased the risk further, reflecting the period of the year of maximum transmission. This was seen with as viruses with a clear seasonality but not with viruses with atypical or absent seasonality.

Bats (order Chiroptera) are known as natural reservoir hosts of many emerging zoonotic diseases. The increasing trend in outbreaks of bat-borne emerging zoonotic diseases in recent years poses serious risks to public health. Coronaviruses in bat populations have demonstrated their potential to bring about deadly pandemics, such as SARS (severe acute respiratory syndrome) and MERS (Middle East respiratory syndrome). Hendra virus in Pteropus spp. (fruit bats or flying foxes) is a lethal zoonotic virus that has repeatedly emerged to infect horses, leading to fatal human infections in eastern Australia. However, more research has been needed on mechanisms how bats maintain zoonotic pathogens in their populations and on factors that stimulate the reservoir hosts to excrete the pathogens. This knowledge would help understand the spillover mechanism and manage the diseases effectively in their natural reservoir hosts before the diseases spillover. This thesis explores the transmission dynamics of bat-borne viruses (coronavirus and Hendra virus) in their natural reservoir hosts of bats, by employing mathematical epidemic models to simulate the dynamics. Chapter 1 commences with the story of the emergence of Hendra virus. From the story, particular questions are extracted. I review the knowledge previously available to answer those questions and explain how approaches for mathematical modelling of infectious diseases can be used to study these topics. Relevant information on bat biology and ecology is suggested. Management strategies for bat zoonotic diseases are also previewed. Finally, the aims and structure of the thesis are outlined. Chapter 2 analyses the effect of persistent infection on coronavirus maintenance in a population of Australian bats (Myotis macropus). By using a previously performed capture-mark-recapture (CMR) study, more intensive mathematical methods were employed. The multi-model selection processes supported the notion that it is appropriate to divide coronavirus infectious bats into two groups of persistently infectious and transiently infectious bats, based on the infectious period. The epidemic models predicted that the grouping of bats increases the probability of coronavirus maintenance in the bat population. Chapter 3 explores the effects of maternally-derived immunity in seasonally breeding wildlife on epidemic patterns by using a system of Hendra virus infection in black flying foxes (Pteropus alecto). Deterministic models were used to simulate epidemics, which were characterised by a variety of timings of viral introduction and a range of pre-existing herd immunities. Waning maternally-derived immunity dispersed the timing of supply of susceptible individuals from births and losses of maternally-derived immunity and thereby diluted the effect of seasonal breeding on epidemics. The dispersion of timing increased the probability of viral persistence and contributed to shifting the timing of epidemic peaks further away from the peak of a birth pulse. Chapter 4 numerically examines whether a metapopulation of flying foxes (Pteropus spp.) can support the maintenance of Hendra virus. The implications of metapopulation structure of flying foxes on Hendra virus dynamics needs more investigations. A single population of flying foxes in the context of a metapopulation structure was stochastically simulated to repeat the cycle of viral extinction and recolonisation in the population. The simulation results predicted that viral recolonisation should occur more frequently than extinction in a colony in a metapopulation, supporting the hypothesis that the metapopulation structure of flying foxes can maintain long-term persistence of Hendra virus. Chapter 5 examines the effects of culling and dispersal of flying foxes on the spillover risk of Hendra virus. Metapopulation models were simulated stochastically using various culling and dispersal scenarios. The models used the most favourable possible assumptions about Hendra virus epidemiology for the application of these management strategies. Nevertheless, many scenarios were predicted to be counter-productive in reducing the spillover risk of Hendra virus. Even though the scenarios expected positive effects on decreasing the spillover risk, the degree of benefits was not realistic if the cost was considered. I, therefore, concluded that culling or dispersal were not effective strategies to manage Hendra virus spillover. Chapter 6 describes the findings provided in each chapter. Then, I discuss the findings, focusing on the viral dynamics in reservoir populations of emerging infectious diseases. Based on the dynamics, I suggest the disease management strategies. I discuss how to do proper modelling research using insufficient data on wildlife diseases. Finally, this chapter provides suggestions for further research.

Pulmonary tuberculosis (PTB) has been a major threat to global public health. The association between meteorological factors and the incidence of PTB has been widely investigated by the generalized additive model, auto-regressive integrated moving average model and the distributed lag model, etc. However, these models could not address a non-linear or lag correlation between them. In this paper, a penalized distributed lag non-linear model, as a generalized and improved one, was applied to explore the influence of meteorological factors (such as air temperature, relative humidity and wind speed) on the PTB incidence in Xinjiang from 2004 to 2019. Moreover, we firstly use a comprehensive index (apparent temperature, AT) to access the impact of multiple meteorological factors on the incidence of PTB. It was found that the relationships between air temperature, relative humidity, wind speed, AT and PTB incidence were nonlinear (showed “wave-type “, “invested U-type”, “U-type” and “wave-type”, respectively). When air temperature at the lowest value (−16.1 °C) could increase the risk of PTB incidence with the highest relative risk (RR = 1.63, 95% CI: 1.21–2.20). An assessment of relative humidity demonstrated an increased risk of PTB incidence between 44.5% and 71.8% with the largest relative risk (RR = 1.49, 95% CI: 1.32–1.67) occurring at 59.2%. Both high and low wind speeds increased the risk of PTB incidence, especially at the lowest wind speed 1.4 m/s (RR = 2.20, 95% CI: 1.95–2.51). In particular, the lag effects of low and high AT on PTB incidence were nonlinear. The lag effects of extreme cold AT (−18.5 °C, 1st percentile) on PTB incidence reached a relative risk peak (RR = 2.18, 95% CI: 2.06–2.31) at lag 1 month. Overall, it was indicated that the environment with low air temperature, suitable relative humidity and wind speed is more conducive to the transmission of PTB, and low AT is associated significantly with increased risk of PTB in Xinjiang.

HIV/AIDS is an infectious disease threating human health all over the world. Central Java Province ranks as 6th in terms of the most HIV/AIDS cases in Indonesia. A precise disease control is needed to monitor the spreading of disease infection. A mathematical model which works based on the changing from susceptible into the infected population is needed. In this research, SIR (Susceptible, Infected, Removed) model is used to empirically understand of HIV dispersion cases and HIV/AIDS endemicity in Central Java. The demographic data and the number of HIV/AIDS cases in 2010 to 2014 are used as the dataset. The result shows that HIV/AIDS infection model in Central Java is y=0.6e^-0.125x , where y is the number of infectious and x is the spreading time. The result shows the average data test error is 13%, and the potential endemic regions having R 0 >1 are Cilacap Regency and Semarang City respectively.

Climate change and air pollution have significantly influenced disease prevalence and transmission. Human adenovirus (HAdV) is a common pathogen that causes acute respiratory infections in children. This study employed an ecological approach to investigate the relationship between HAdV infection in children in Lanzhou, Northwest China, and meteorological factors and air pollutants, aiming to deepen the understanding of environmental factors affecting viral transmission. Clinical specimens from children with acute respiratory infections were collected at a sentinel hospital in Lanzhou from January 1, 2023, to February 28, 2025, and were subjected to respiratory adenovirus nucleic acid testing. HAdV infection patterns were analyzed according to age, sex, and season. A combined approach of stepwise linear regression and generalized additive models (GAM) was employed to investigate the correlations between HAdV infection and meteorological factors/air pollutants from January 1, 2023, to December 31, 2024. Between January 1, 2023, and February 28, 2025, a total of 1,339 throat swab specimens were collected from children with acute respiratory infections (ARIs), with a male-to-female ratio of 1.48:1. The HAdV incidence rate in 2024 (11.23%) was higher than that in 2023 (5.45%). The HAdV incidence rates among male and female children were 5.15% and 3.73%, respectively. Preschool-and school-aged children exhibited higher incidence rates than infants and toddlers, at 3.29%, 3.36%, 0.75%, and 1.49%, respectively. HAdV circulated throughout all four seasons, with peak prevalence in autumn (2.28%) and winter (5.06%). HAdV incidence rates showed significant negative correlations with meteorological factors (air temperature, sunshine duration, wind speed), with correlation coefficients of: r = -0.6398 (95% CI: -0.8878, -0.1042), (P = 0.0250); r=-0.6376 (95% CI: -0.8870, -0.1005), (P = 0.0257); r=-0.6208 (95% CI: -0.8809, -0.07285), (P = 0.0312); showed significant positive correlations with atmospheric pollutants (CO, NO₂, and SO₂), with correlation coefficients of: r = 0.7610 (95% CI: 0.3321, 0.9291), (P = 0.0040); r = 0.6846 (95% CI: 0.1824, 0.9035), (P = 0.0140); r = 0.7162 (95% CI: 0.2147, 0.9143), (P = 0.0088); while exhibiting a significant negative correlation with atmospheric pollutant O₃, with a correlation coefficient of r = -0.6938 (95% CI: -0.9067, -0.1992), (P = 0.0123). GAM analysis revealed that meteorological factors (air temperature, sunshine duration, and wind speed) were all nonlinearly associated with adenovirus incidence rates. HAdV was detected at a higher rate in children in the preschool and school-age groups, and most cases were detected in the fall and winter seasons. The incidence rate of HAdV was negatively correlated with meteorological factors (temperature, hours of sunshine, and wind speed) and the atmospheric pollutant O₃, and positively correlated with atmospheric pollutants (CO, NO₂, and SO₂). The influence of these pollutants on the prevalence of HAdV infection should not be ignored.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-24515-5.