1
|
Ji H, Li K, Shang M, Wang Z, Liu Q. The 2016 Severe Floods and Incidence of Hemorrhagic Fever With Renal Syndrome in the Yangtze River Basin. JAMA Netw Open 2024; 7:e2429682. [PMID: 39172449 PMCID: PMC11342140 DOI: 10.1001/jamanetworkopen.2024.29682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 06/28/2024] [Indexed: 08/23/2024] Open
Abstract
Importance Hemorrhagic fever with renal syndrome (HFRS), a neglected zoonotic disease, has received only short-term attention in postflood prevention and control initiatives, possibly because of a lack of evidence regarding the long-term association of flooding with HFRS. Objectives To quantify the association between severe floods and long-term incidence of HFRS in the Yangtze River basin and to examine the modifying role of geographical factors in this association. Design, Setting, and Participants This cross-sectional study collected data on HFRS cases between July 1, 2013, and June 30, 2019, from 58 cities in 4 provinces (Anhui, Hubei, Hunan, and Jiangxi) in the Yangtze River basin of China, with a breakpoint of flooding in July 2016, generating monthly data. The 3 years after July 2016 were defined as the postflood period, while the 3 years before the breakpoint were defined as the control period. Statistical analysis was performed from October to December 2023. Exposures City-level monthly flooding, elevation, ruggedness index, and closest distance from each city to the Yangtze River and its tributaries. Main Outcomes and Measures The primary outcomes were the number of city-level monthly HFRS cases and the number of type 1 (spring or summer) and type 2 (autumn or winter) HFRS cases. Results A total of 11 745 patients with HFRS were reported during the study period: 5216 patients (mean [SD] age, 47.1 [16.2] years; 3737 men [71.6%]) in the control period and 6529 patients (mean [SD] age, 49.8 [15.8] years; 4672 men [71.6%]) in the postflood period. The pooled effects of interrupted time series analysis indicated a long-term association between flooding and HFRS incidence (odds ratio, 1.38; 95% CI, 1.13-1.68), with type 1 cases being at highest risk (odds ratio, 1.71; 95% CI, 1.40-2.09). The metaregression results indicated that elevation and ruggedness index were negatively associated with the risk of HFRS, while the distance to rivers interacted with these associations. Conclusions and Relevance This cross-sectional study of the long-term association between flooding and HFRS incidence, as well as the modification effects of geographical factors, suggests that severe floods were associated with an increased risk of HFRS within 3 years. This study provides evidence for the development of HFRS prevention and control strategies after floods.
Collapse
Affiliation(s)
- Haoqiang Ji
- Department of Vector Control, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong Province, Jinan, People’s Republic of China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping District, Beijing, People’s Republic of China
- World Health Organization Collaborating Centre for Vector Surveillance and Management, Changping District, Beijing, People’s Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong Province, Jinan, People’s Republic of China
- Shandong University Climate Change and Health Center, Shandong Province, Jinan, People’s Republic of China
| | - Ke Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping District, Beijing, People’s Republic of China
- World Health Organization Collaborating Centre for Vector Surveillance and Management, Changping District, Beijing, People’s Republic of China
| | - Meng Shang
- Department of Vector Control, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong Province, Jinan, People’s Republic of China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping District, Beijing, People’s Republic of China
- World Health Organization Collaborating Centre for Vector Surveillance and Management, Changping District, Beijing, People’s Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong Province, Jinan, People’s Republic of China
- Shandong University Climate Change and Health Center, Shandong Province, Jinan, People’s Republic of China
| | - Zhenxu Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping District, Beijing, People’s Republic of China
- World Health Organization Collaborating Centre for Vector Surveillance and Management, Changping District, Beijing, People’s Republic of China
| | - Qiyong Liu
- Department of Vector Control, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong Province, Jinan, People’s Republic of China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping District, Beijing, People’s Republic of China
- World Health Organization Collaborating Centre for Vector Surveillance and Management, Changping District, Beijing, People’s Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong Province, Jinan, People’s Republic of China
- Shandong University Climate Change and Health Center, Shandong Province, Jinan, People’s Republic of China
| |
Collapse
|
2
|
Luo Y, Zhang L, Xu Y, Kuai Q, Li W, Wu Y, Liu L, Ren J, Zhang L, Shi Q, Liu X, Tan W. Epidemic Characteristics and Meteorological Risk Factors of Hemorrhagic Fever With Renal Syndrome in 151 Cities in China From 2015 to 2021: Retrospective Analysis. JMIR Public Health Surveill 2024; 10:e52221. [PMID: 38837197 PMCID: PMC11187512 DOI: 10.2196/52221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 12/20/2023] [Accepted: 04/29/2024] [Indexed: 06/06/2024] Open
Abstract
BACKGROUND Hemorrhagic fever with renal syndrome (HFRS) continues to pose a significant public health threat to the population in China. Previous epidemiological evidence indicates that HFRS is climate sensitive and influenced by meteorological factors. However, past studies either focused on too-narrow geographical regions or investigated time periods that were too early. There is an urgent need for a comprehensive analysis to interpret the epidemiological patterns of meteorological factors affecting the incidence of HFRS across diverse climate zones. OBJECTIVE In this study, we aimed to describe the overall epidemic characteristics of HFRS and explore the linkage between monthly HFRS cases and meteorological factors at different climate levels in China. METHODS The reported HFRS cases and meteorological data were collected from 151 cities in China during the period from 2015 to 2021. We conducted a 3-stage analysis, adopting a distributed lag nonlinear model and a generalized additive model to estimate the interactions and marginal effects of meteorological factors on HFRS. RESULTS This study included a total of 63,180 cases of HFRS; the epidemic trends showed seasonal fluctuations, with patterns varying across different climate zones. Temperature had the greatest impact on the incidence of HFRS, with the maximum hysteresis effects being at 1 month (-19 ºC; relative risk [RR] 1.64, 95% CI 1.24-2.15) in the midtemperate zone, 0 months (28 ºC; RR 3.15, 95% CI 2.13-4.65) in the warm-temperate zone, and 0 months (4 ºC; RR 1.72, 95% CI 1.31-2.25) in the subtropical zone. Interactions were discovered between the average temperature, relative humidity, and precipitation in different temperature zones. Moreover, the influence of precipitation and relative humidity on the incidence of HFRS had different characteristics under different temperature layers. The hysteresis effect of meteorological factors did not end after an epidemic season, but gradually weakened in the following 1 or 2 seasons. CONCLUSIONS Weather variability, especially low temperature, plays an important role in epidemics of HFRS in China. A long hysteresis effect indicates the necessity of continuous intervention following an HFRS epidemic. This finding can help public health departments guide the prevention and control of HFRS and develop strategies to cope with the impacts of climate change in specific regions.
Collapse
Affiliation(s)
- Yizhe Luo
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Longyao Zhang
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yameng Xu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Qiyuan Kuai
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Wenhao Li
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Yifan Wu
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Licheng Liu
- Jiangsu Macro and Micro Test Med-tech Co, Ltd, Nantong, China
| | - Jiarong Ren
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China, Beijing, China
| | - Lingling Zhang
- College of Life Science, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Qiufang Shi
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xiaobo Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China, Beijing, China
- Department of Vector Control, School of Public Health, Shandong University, Jinan, China
- Xinjiang Key Laboratory of Vector-borne Infectious Diseases, Urumqi, China
| | - Weilong Tan
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| |
Collapse
|
3
|
Moser SK, Spencer JA, Barnard M, Hyman JM, Manore CA, Gorris ME. Exploring Climate-Disease Connections in Geopolitical Versus Ecological Regions: The Case of West Nile Virus in the United States. GEOHEALTH 2024; 8:e2024GH001024. [PMID: 38912225 PMCID: PMC11190782 DOI: 10.1029/2024gh001024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 05/31/2024] [Accepted: 06/03/2024] [Indexed: 06/25/2024]
Abstract
Many infectious disease forecasting models in the United States (US) are built with data partitioned into geopolitical regions centered on human activity as opposed to regions defined by natural ecosystems; although useful for data collection and intervention, this has the potential to mask biological relationships between the environment and disease. We explored this concept by analyzing the correlations between climate and West Nile virus (WNV) case data aggregated to geopolitical and ecological regions. We compared correlations between minimum, maximum, and mean annual temperature; precipitation; and annual WNV neuroinvasive disease (WNND) case data from 2005 to 2019 when partitioned into (a) climate regions defined by the National Oceanic and Atmospheric Administration (NOAA) and (b) Level I ecoregions defined by the Environmental Protection Agency (EPA). We found that correlations between climate and WNND in NOAA climate regions and EPA ecoregions were often contradictory in both direction and magnitude, with EPA ecoregions more often supporting previously established biological hypotheses and environmental dynamics underlying vector-borne disease transmission. Using ecological regions to examine the relationships between climate and disease cases can enhance the predictive power of forecasts at various scales, motivating a conceptual shift in large-scale analyses from geopolitical frameworks to more ecologically meaningful regions.
Collapse
Affiliation(s)
- S. Kane Moser
- Genomics and BioanalyticsLos Alamos National LaboratoryLos AlamosNMUSA
- Odum School of EcologyUniversity of GeorgiaAthensGAUSA
| | - Julie A. Spencer
- Information Systems and ModelingLos Alamos National LaboratoryLos AlamosNMUSA
| | - Martha Barnard
- Information Systems and ModelingLos Alamos National LaboratoryLos AlamosNMUSA
- Division of BiostatisticsUniversity of MinnesotaMinneapolisMNUSA
| | | | - Carrie A. Manore
- Theoretical Biology and BiophysicsLos Alamos National LaboratoryLos AlamosNMUSA
| | - Morgan E. Gorris
- Information Systems and ModelingLos Alamos National LaboratoryLos AlamosNMUSA
| |
Collapse
|
4
|
Maroli M, Bellomo CM, Coelho RM, Martinez VP, Piña CI, Gómez Villafañe IE. Orthohantavirus Infection in Two Rodent Species that Inhabit Wetlands in Argentina. ECOHEALTH 2023; 20:402-415. [PMID: 38091181 DOI: 10.1007/s10393-023-01661-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 09/30/2023] [Indexed: 02/21/2024]
Abstract
Previous research conducted in central-east region of Argentina recorded potential orthohantavirus host rodents in diverse environments, but no research has focused particularly on islands, the environments that present the greatest risk to humans. For this reason, the aims of this research were to determine the orthohantavirus host in the rodent community focused on islands of Paraná River Delta, central-east region of Argentina, to identify temporal and spatial factors associated with orthohantavirus prevalence variations, to compare the functional traits of seropositive and seronegative rodents, and to explore the association between orthohantavirus prevalence and rodent community characteristics between August 2014 and May 2018. With a trapping effort of 14,600 trap-nights, a total of 348 sigmodontine rodent specimens belonging to seven species were captured 361 times. The overall antibody prevalence was 4.9%. Particularly, 14.9% of Oligoryzomys flavescens and 1.5% of Oxymycterus rufus, mainly reproductively active adult males, had antibodies against orthohantavirus. Even though O. flavescens inhabit all islands, our results suggest spatial heterogeneity in the viral distribution, with two months after periods of low temperature presenting increases in seroprevalence. This could be a response to the increased proportion of adults present in the rodent population. In addition, an association was found between the high seroprevalence and the diversity of the rodent assemblage. We also found 1.5% of O. rufus exposed to orthohantavirus, which shows us that further investigation of the ecology of the virus is needed to answer whether this species act as a spillover or a new competent host.
Collapse
Affiliation(s)
- Malena Maroli
- Facultad de Ciencia y Tecnología, Universidad Autónoma de Entre Ríos, 3105, Diamante, Entre Ríos, Argentina
| | - Carla M Bellomo
- Instituto Nacional de Enfermedades Infecciosas Administración Nacional de Laboratorios e Institutos de Salud Dr. Carlos G. Malbrán, Buenos Aires, Argentina
| | - Rocío M Coelho
- Instituto Nacional de Enfermedades Infecciosas Administración Nacional de Laboratorios e Institutos de Salud Dr. Carlos G. Malbrán, Buenos Aires, Argentina
| | - Valeria P Martinez
- Instituto Nacional de Enfermedades Infecciosas Administración Nacional de Laboratorios e Institutos de Salud Dr. Carlos G. Malbrán, Buenos Aires, Argentina
| | - Carlos I Piña
- Centro de Investigación Científica y de Transferencia Tecnológica a la Producción-Consejo Nacional de Investigaciones Científicas y Técnicas, Facultad de Ciencia y Tecnología, Universidad Autónoma de Entre Ríos, 3105, Diamante, Entre Ríos, Argentina
| | - Isabel E Gómez Villafañe
- Instituto de Ecología, Facultad de Ciencias Exactas y Naturales, Genética y Evolución de Buenos Aires (CONICET-UBA), Universidad de Buenos Aires, Intendente Güiraldes 2160, Ciudad Universitaria, C1428EGA, Ciudad Autónoma de Buenos Aires, Argentina.
| |
Collapse
|
5
|
Palmeiro-Silva YK, Lescano AG, Flores EC, Astorga E Y, Rojas L, Chavez MG, Mora-Rivera W, Hartinger SM. Identifying gaps on health impacts, exposures, and vulnerabilities to climate change on human health and wellbeing in South America: a scoping review. LANCET REGIONAL HEALTH. AMERICAS 2023; 26:100580. [PMID: 37876675 PMCID: PMC10593580 DOI: 10.1016/j.lana.2023.100580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 05/29/2023] [Accepted: 08/04/2023] [Indexed: 10/26/2023]
Abstract
There is an important gap in regional information on climate change and health, limiting the development of science-based climate policies in South American countries. This study aims to identify the main gaps in the existing scientific literature on the impacts, exposure, and vulnerabilities of climate change on population health. A scoping review was performed guided by four sub-questions focused on the impacts of climate change on physical and mental health, exposure and vulnerability factors of population to climate hazards. The main findings showed that physical impacts mainly included infectious diseases, while mental health impacts included trauma, depression, and anxiety. Evidence on population exposure to climate hazards is limited, and social determinants of health and individual factors were identified as vulnerability factors. Overall, evidence on the intersection between climate change and health is limited in South America and has been generated in silos, with limited transdisciplinary research. More formal and systematic information should be generated to inform public policy. Funding None.
Collapse
Affiliation(s)
- Yasna K. Palmeiro-Silva
- Institute for Global Health, University College London, London, United Kingdom
- Centro de Políticas Públicas, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Andres G. Lescano
- Clima, Latin American Center of Excellence for Climate Change and Health, Universidad Peruana Cayetano Heredia, Lima, Peru
- Emerge, Emerging Diseases and Climate Change Research Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Elaine C. Flores
- Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
- The Stanford Center for Innovation in Global Health, Stanford University, Stanford, CA, USA
| | - Yamileth Astorga E
- Escuela de Tecnologías en Salud, Universidad de Costa Rica, San Pedro, San José, Costa Rica
| | - Luciana Rojas
- Clima, Latin American Center of Excellence for Climate Change and Health, Universidad Peruana Cayetano Heredia, Lima, Peru
- Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Mario G. Chavez
- Emerge, Emerging Diseases and Climate Change Research Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru
- Sociedad Científica de San Fernando, Universidad Nacional Mayor de San Marcos, Lima, Peru
| | - Wendel Mora-Rivera
- InterAmerican Center for Global Health (CISG), Puntarenas, Costa Rica
- Escuela de Enfermería, Universidad Latina de Costa Rica, San José, Costa Rica
| | - Stella M. Hartinger
- Clima, Latin American Center of Excellence for Climate Change and Health, Universidad Peruana Cayetano Heredia, Lima, Peru
| |
Collapse
|
6
|
Marie V, Gordon ML. The (Re-)Emergence and Spread of Viral Zoonotic Disease: A Perfect Storm of Human Ingenuity and Stupidity. Viruses 2023; 15:1638. [PMID: 37631981 PMCID: PMC10458268 DOI: 10.3390/v15081638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 07/22/2023] [Accepted: 07/25/2023] [Indexed: 08/27/2023] Open
Abstract
Diseases that are transmitted from vertebrate animals to humans are referred to as zoonotic diseases. Although microbial agents such as bacteria and parasites are linked to zoonotic events, viruses account for a high percentage of zoonotic diseases that have emerged. Worryingly, the 21st century has seen a drastic increase in the emergence and re-emergence of viral zoonotic disease. Even though humans and animals have coexisted for millennia, anthropogenic factors have severely increased interactions between the two populations, thereby increasing the risk of disease spill-over. While drivers such as climate shifts, land exploitation and wildlife trade can directly affect the (re-)emergence of viral zoonotic disease, globalisation, geopolitics and social perceptions can directly facilitate the spread of these (re-)emerging diseases. This opinion paper discusses the "intelligent" nature of viruses and their exploitation of the anthropogenic factors driving the (re-)emergence and spread of viral zoonotic disease in a modernised and connected world.
Collapse
Affiliation(s)
- Veronna Marie
- Microbiology Laboratory, Department of Analytical Services, Rand Water, Vereeniging 1939, South Africa
| | - Michelle L. Gordon
- School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu-Natal, Durban 4001, South Africa;
| |
Collapse
|
7
|
López WR, Altamiranda-Saavedra M, Kehl SD, Ferro I, Bellomo C, Martínez VP, Simoy MI, Gil JF. Modeling potential risk areas of Orthohantavirus transmission in Northwestern Argentina using an ecological niche approach. BMC Public Health 2023; 23:1236. [PMID: 37365559 DOI: 10.1186/s12889-023-16071-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 06/07/2023] [Indexed: 06/28/2023] Open
Abstract
BACKGROUND Hantavirus Pulmonary Syndrome (HPS) is a rodent-borne zoonosis in the Americas, with up to 50% mortality rates. In Argentina, the Northwestern endemic area presents half of the annually notified HPS cases in the country, transmitted by at least three rodent species recognized as reservoirs of Orthohantavirus. The potential distribution of reservoir species based on ecological niche models (ENM) can be a useful tool to establish risk areas for zoonotic diseases. Our main aim was to generate an Orthohantavirus risk transmission map based on ENM of the reservoir species in northwest Argentina (NWA), to compare this map with the distribution of HPS cases; and to explore the possible effect of climatic and environmental variables on the spatial variation of the infection risk. METHODS Using the reservoir geographic occurrence data, climatic/environmental variables, and the maximum entropy method, we created models of potential geographic distribution for each reservoir in NWA. We explored the overlap of the HPS cases with the reservoir-based risk map and a deforestation map. Then, we calculated the human population at risk using a census radius layer and a comparison of the environmental variables' latitudinal variation with the distribution of HPS risk. RESULTS We obtained a single best model for each reservoir. The temperature, rainfall, and vegetation cover contributed the most to the models. In total, 945 HPS cases were recorded, of which 97,85% were in the highest risk areas. We estimated that 18% of the NWA population was at risk and 78% of the cases occurred less than 10 km from deforestation. The highest niche overlap was between Calomys fecundus and Oligoryzomys chacoensis. CONCLUSIONS This study identifies potential risk areas for HPS transmission based on climatic and environmental factors that determine the distribution of the reservoirs and Orthohantavirus transmission in NWA. This can be used by public health authorities as a tool to generate preventive and control measures for HPS in NWA.
Collapse
Affiliation(s)
- Walter R López
- Instituto de Investigaciones de Enfermedades Tropicales (IIET), Universidad Nacional de Salta (UNSa), Sede Regional Orán, A4400, Salta, Argentina
| | - Mariano Altamiranda-Saavedra
- Grupo de Investigación Bioforense, Facultad de Derecho Y Ciencias Forenses, Tecnológico de Antioquia Institución Universitaria, Antioquia, Colombia
| | - Sebastián D Kehl
- Instituto Nacional de Enfermedades Infecciosas (INEI), Administración Nacional de Laboratorios E Institutos de Salud (ANLIS) "Dr. C. G. Malbrán", Buenos Aires, Argentina
| | - Ignacio Ferro
- Instituto de Ecorregiones Andinas (INECOA), Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), Universidad Nacional de Jujuy (UNJu), San Salvador de Jujuy, Argentina
| | - Carla Bellomo
- Instituto Nacional de Enfermedades Infecciosas (INEI), Administración Nacional de Laboratorios E Institutos de Salud (ANLIS) "Dr. C. G. Malbrán", Buenos Aires, Argentina
| | - Valeria P Martínez
- Instituto Nacional de Enfermedades Infecciosas (INEI), Administración Nacional de Laboratorios E Institutos de Salud (ANLIS) "Dr. C. G. Malbrán", Buenos Aires, Argentina
| | - Mario I Simoy
- Instituto de Investigaciones en Energía No Convencional (INENCO), Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), Universidad Nacional de Salta (UNSa), A4400, Salta, Argentina
- Instituto Multidisciplinario Sobre Ecosistemas Y Desarrollo Sustentable (UNCPBA - CICPBA), Tandil, Argentina
| | - José F Gil
- Instituto de Investigaciones de Enfermedades Tropicales (IIET), Universidad Nacional de Salta (UNSa), Sede Regional Orán, A4400, Salta, Argentina.
- Instituto de Investigaciones en Energía No Convencional (INENCO), Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), Universidad Nacional de Salta (UNSa), A4400, Salta, Argentina.
- Cátedra de Química Biológica Y Biología Molecular de La Facultad de Ciencias Naturales, Universidad Nacional de Salta, A4400, Salta, Argentina.
| |
Collapse
|
8
|
Han L, Sun Z, Li Z, Zhang Y, Tong S, Qin T. Impacts of meteorological factors on the risk of scrub typhus in China, from 2006 to 2020: A multicenter retrospective study. Front Microbiol 2023; 14:1118001. [PMID: 36910234 PMCID: PMC9996048 DOI: 10.3389/fmicb.2023.1118001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 02/08/2023] [Indexed: 02/25/2023] Open
Abstract
Scrub typhus is emerging as a global public health threat owing to its increased prevalence and remarkable geographic expansion. However, it remains a neglected disease, and possible influences of meteorological factors on its risk are poorly understood. We conducted the largest-scale research to assess the impact of meteorological factors on scrub typhus in China. Weekly data on scrub typhus cases and meteorological factors were collected across 59 prefecture-level administrative regions from 2006 to 2020. First, we divided these regions into 3 regions and analyzed the epidemiological characteristics of scrub typhus. We then applied the distributed lag nonlinear model, combined with multivariate meta-analysis, to examine the associations between meteorological factors and scrub typhus incidence at the total and regional levels. Subsequently, we identified the critical meteorological predictors of scrub typhus incidence and extracted climate risk windows. We observed distinct epidemiological characteristics across regions, featuring obvious clustering in the East and Southwest with more even distribution and longer epidemic duration in the South. The mean temperature and relative humidity had profound effects on scrub typhus with initial-elevated-descendent patterns. Weather conditions of weekly mean temperatures of 25-33°C and weekly relative humidity of 60-95% were risk windows for scrub typhus. Additionally, the heavy rainfall was associated with sharp increase in scrub typhus incidence. We identified specific climatic signals to detect the epidemic of scrub typhus, which were easily monitored to generalize. Regional heterogeneity should be considered for targeted monitoring and disease control strategies.
Collapse
Affiliation(s)
- Ling Han
- State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhaobin Sun
- Institute of Urban Meteorology, China Meteorological Administration, Beijing, China.,China Meteorological Administration Urban Meteorology Key Laboratory, Beijing, China
| | - Ziming Li
- Institute of Urban Meteorology, China Meteorological Administration, Beijing, China
| | - Yunfei Zhang
- State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shilu Tong
- Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China.,Center for Global Health, Nanjing Medical University, Nanjing, China.,School of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD, Australia
| | - Tian Qin
- State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| |
Collapse
|
9
|
Meteorological change and hemorrhagic fever with renal syndrome epidemic in China, 2004-2018. Sci Rep 2022; 12:20037. [PMID: 36414682 PMCID: PMC9681842 DOI: 10.1038/s41598-022-23945-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 11/08/2022] [Indexed: 11/23/2022] Open
Abstract
Hemorrhagic fever with renal syndrome (HFRS), caused by hantavirus, is a serious public health problem in China. Despite intensive countermeasures including Patriotic Health Campaign, rodent control and vaccination in affected areas, HFRS is still a potential public health threat in China, with more than 10,000 new cases per year. Previous epidemiological evidence suggested that meteorological factors could influence HFRS incidence, but the studies were mainly limited to a specific city or region in China. This study aims to evaluate the association between monthly HFRS cases and meteorological change at the country level using a multivariate distributed lag nonlinear model (DLNM) from 2004 to 2018. The results from both univariate and multivariate models showed a non-linear cumulative relative risk relationship between meteorological factors (with a lag of 0-6 months) such as mean temperature (Tmean), precipitation, relative humidity (RH), sunshine hour (SH), wind speed (WS) and HFRS incidence. The risk for HFRS cases increased steeply as the Tmean between - 23 and 14.79 °C, SH between 179.4 and 278.4 h and RH remaining above 69% with 50-95 mm precipitation and 1.70-2.00 m/s WS. In conclusion, meteorological factors such as Tmean and RH showed delayed-effects on the increased risk of HFRS in the study and the lag varies across climate factors. Temperature with a lag of 6 months (RR = 3.05) and precipitation with a lag of 0 months (RR = 2.08) had the greatest impact on the incidence of HFRS.
Collapse
|
10
|
Wang Y, Wei X, Xiao X, Yin W, He J, Ren Z, Li Z, Yang M, Tong S, Guo Y, Zhang W, Wang Y. Climate and socio-economic factors drive the spatio-temporal dynamics of HFRS in Northeastern China. One Health 2022; 15:100466. [DOI: 10.1016/j.onehlt.2022.100466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 11/15/2022] [Accepted: 11/20/2022] [Indexed: 11/23/2022] Open
|
11
|
Molina-Guzmán LP, Gutiérrez-Builes LA, Ríos-Osorio LA. Models of spatial analysis for vector-borne diseases studies: A systematic review. Vet World 2022; 15:1975-1989. [PMID: 36313837 PMCID: PMC9615510 DOI: 10.14202/vetworld.2022.1975-1989] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 06/24/2022] [Indexed: 11/16/2022] Open
Abstract
Background and Aim: Vector-borne diseases (VBDs) constitute a global problem for humans and animals. Knowledge related to the spatial distribution of various species of vectors and their relationship with the environment where they develop is essential to understand the current risk of VBDs and for planning surveillance and control strategies in the face of future threats. This study aimed to identify models, variables, and factors that may influence the emergence and resurgence of VBDs and how these factors can affect spatial local and global distribution patterns.
Materials and Methods: A systematic review was designed based on identification, screening, selection, and inclusion described in the research protocols according to the preferred reporting items for systematic reviews and meta-analyses guide. A literature search was performed in PubMed, ScienceDirect, Scopus, and SciELO using the following search strategy: Article type: Original research, Language: English, Publishing period: 2010–2020, Search terms: Spatial analysis, spatial models, VBDs, climate, ecologic, life cycle, climate variability, vector-borne, vector, zoonoses, species distribution model, and niche model used in different combinations with "AND" and "OR."
Results: The complexity of the interactions between climate, biotic/abiotic variables, and non-climate factors vary considerably depending on the type of disease and the particular location. VBDs are among the most studied types of illnesses related to climate and environmental aspects due to their high disease burden, extended presence in tropical and subtropical areas, and high susceptibility to climate and environment variations.
Conclusion: It is difficult to generalize our knowledge of VBDs from a geospatial point of view, mainly because every case is inherently independent in variable selection, geographic coverage, and temporal extension. It can be inferred from predictions that as global temperatures increase, so will the potential trend toward extreme events. Consequently, it will become a public health priority to determine the role of climate and environmental variations in the incidence of infectious diseases. Our analysis of the information, as conducted in this work, extends the review beyond individual cases to generate a series of relevant observations applicable to different models.
Collapse
Affiliation(s)
- Licet Paola Molina-Guzmán
- Grupo Biología de Sistemas, Escuela de Ciencias de la Salud, Facultad de Medicina, Universidad Pontificia Bolivariana, Medellín, Colombia; Grupo de Investigación Salud y Sostenibilidad, Escuela de Microbiología, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellin - Colombia
| | - Lina A. Gutiérrez-Builes
- Grupo Biología de Sistemas, Escuela de Ciencias de la Salud, Facultad de Medicina, Universidad Pontificia Bolivariana, Medellín, Colombia
| | - Leonardo A. Ríos-Osorio
- Grupo de Investigación Salud y Sostenibilidad, Escuela de Microbiología, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellin - Colombia
| |
Collapse
|
12
|
Douglas KO, Payne K, Sabino-Santos G, Agard J. Influence of Climatic Factors on Human Hantavirus Infections in Latin America and the Caribbean: A Systematic Review. Pathogens 2021; 11:pathogens11010015. [PMID: 35055965 PMCID: PMC8778283 DOI: 10.3390/pathogens11010015] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 12/16/2021] [Accepted: 12/17/2021] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND With the current climate change crisis and its influence on infectious disease transmission there is an increased desire to understand its impact on infectious diseases globally. Hantaviruses are found worldwide, causing infectious diseases such as haemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS)/hantavirus pulmonary syndrome (HPS) in tropical regions such as Latin America and the Caribbean (LAC). These regions are inherently vulnerable to climate change impacts, infectious disease outbreaks and natural disasters. Hantaviruses are zoonotic viruses present in multiple rodent hosts resident in Neotropical ecosystems within LAC and are involved in hantavirus transmission. METHODS We conducted a systematic review to assess the association of climatic factors with human hantavirus infections in the LAC region. Literature searches were conducted on MEDLINE and Web of Science databases for published studies according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) criteria. The inclusion criteria included at least eight human hantavirus cases, at least one climatic factor and study from > 1 LAC geographical location. RESULTS In total, 383 papers were identified within the search criteria, but 13 studies met the inclusion criteria ranging from Brazil, Chile, Argentina, Bolivia and Panama in Latin America and a single study from Barbados in the Caribbean. Multiple mathematical models were utilized in the selected studies with varying power to generate robust risk and case estimates of human hantavirus infections linked to climatic factors. Strong evidence of hantavirus disease association with precipitation and habitat type factors were observed, but mixed evidence was observed for temperature and humidity. CONCLUSIONS The interaction of climate and hantavirus diseases in LAC is likely complex due to the unknown identity of all vertebrate host reservoirs, circulation of multiple hantavirus strains, agricultural practices, climatic changes and challenged public health systems. There is an increasing need for more detailed systematic research on the influence of climate and other co-related social, abiotic, and biotic factors on infectious diseases in LAC to understand the complexity of vector-borne disease transmission in the Neotropics.
Collapse
Affiliation(s)
- Kirk Osmond Douglas
- Centre for Biosecurity Studies, Cave Hill Campus, The University of the West Indies, Cave Hill, St. Michael BB11000, Barbados
- Correspondence:
| | - Karl Payne
- Centre for Resource Management and Environmental Studies, Cave Hill Campus, The University of the West Indies, Cave Hill, St. Michael BB11000, Barbados;
| | - Gilberto Sabino-Santos
- School of Public Health and Tropical Medicine, Tulane University, 1324 Tulane Ave Suite 517, New Orleans, LA 70112, USA;
- Centre for Virology Research, Ribeirao Preto Medical School, University of Sao Paulo, 3900 Av. Bandeirantes, Ribeirao Preto 14049-900, SP, Brazil
| | - John Agard
- Department of Life Sciences, The University of the West Indies, St. Augustine 999183, Trinidad and Tobago;
| |
Collapse
|
13
|
T-cell epitope-based vaccine designing against Orthohantavirus: a causative agent of deadly cardio-pulmonary disease. NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS 2021; 11:2. [PMID: 34900515 PMCID: PMC8649322 DOI: 10.1007/s13721-021-00339-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/26/2021] [Accepted: 09/28/2021] [Indexed: 12/20/2022]
Abstract
Orthohantavirus, a zoonotic virus responsible for causing human cardio-pulmonary disease, is proven to be a fatal disease. Due to the paucity of regimens to cure the disease and efficient management to eradicate this deadly virus, there is a constant need to expand in-silico approaches belonging to immunology domain to formulate best feasible peptide-based vaccine against it. In lieu of that, we have predicted and validated an epitope of nine-residue-long sequence “MIGLLSSRI”. The predicted epitope has shown best interactions with HLA alleles of MHC Class II proteins, namely HLA DRB1_0101, DRB1_0401, DRB1_0405, DRB1_0701, DRB1_0901, DRB1_1302, and DRB1_1501. The structure of the epitope was modeled by deploying PEPFOLD 3.5 and verified by Ramachandran plot analysis. Molecular docking and simulation studies reveal that this epitope has satisfactory binding scores, ACE value and global energies for docked complexes along with selectable range of RMSD and RMSF values. Also, the predicted epitope “MIGLLSSRI” exhibits population coverage of more than 62% in world population and maximum of 70% in the United States of America. In this intensive study, we have used many tools like AllergenFP, NETMHCII 3.2, VaxiJen, ToxinPred, PEPFOLD 3.5, DINC, IEDB-Population coverage, MHCPred and JCat server. Most of these tools are based on modern innovative statistical algorithms like HMM, ANN, ML, etc. that help in better predictions of putative candidates for vaccine crafting. This innovative methodology is facile, cost-effective and time-efficient, which could facilitate designing of a vaccine against this virus.
Collapse
|