Clusters of spatial, temporal, and space-time distribution of hemorrhagic fever with renal syndrome in Liaoning Province, Northeastern China

<p>Abstract</p> <p>Background</p> <p>Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by Hantavirus, with characteristics of fever, hemorrhage, kidney damage, and hypotension. HFRS is recognized as a notifiable public health problem in China, and Liaoning Province is one of the most seriously affected areas with the most cases in China. It is necessary to investigate the spatial, temporal, and space-time distribution of confirmed cases of HFRS in Liaoning Province, China for future research into risk factors.</p> <p>Methods</p> <p>A cartogram map was constructed; spatial autocorrelation analysis and spatial, temporal, and space-time cluster analysis were conducted in Liaoning Province, China over the period 1988-2001.</p> <p>Results</p> <p>When the number of permutation test was set to 999, Moran's I was 0.3854, and was significant at significance level of 0.001. Spatial cluster analysis identified one most likely cluster and four secondary likely clusters. Temporal cluster analysis identified 1998-2001 as the most likely cluster. Space-time cluster analysis identified one most likely cluster and two secondary likely clusters.</p> <p>Conclusions</p> <p>Spatial, temporal, and space-time scan statistics may be useful in supervising the occurrence of HFRS in Liaoning Province, China. The result of this study can not only assist health departments to develop a better prevention strategy but also potentially increase the public health intervention's effectiveness.</p

Time-Specific Ecologic Niche Models Forecast the Risk of Hemorrhagic Fever with Renal Syndrome in Dongting Lake District, China, 2005–2010

Background: Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne infectious disease, is one of the most serious public health threats in China. Increasing our understanding of the spatial and temporal patterns of HFRS infections could guide local prevention and control strategies. Methodology/Principal Findings: We employed statistical models to analyze HFRS case data together with environmental data from the Dongting Lake district during 2005–2010. Specifically, time-specific ecologic niche models (ENMs) were used to quantify and identify risk factors associated with HFRS transmission as well as forecast seasonal variation in risk across geographic areas. Results showed that the Maximum Entropy model provided the best predictive ability (AUC = 0.755). Time-specific Maximum Entropy models showed that the potential risk areas of HFRS significantly varied across seasons. High-risk areas were mainly found in the southeastern and southwestern areas of the Dongting Lake district. Our findings based on models focused on the spring and winter seasons showed particularly good performance. The potential risk areas were smaller in March, May and August compared with those identified for June, July and October to December. Both normalized difference vegetation index (NDVI) and land use types were found to be the dominant risk factors. Conclusions/Significance: Our findings indicate that time-specific ENMs provide a useful tool to forecast the spatial and temporal risk of HFRS

Análise espacial da hantavirose no Distrito Federal, Brasil

Dissertação (Mestrado em Ciências Ambientais)—Universidade de Brasília, Faculdade UnB Planaltina, Programa de Pós-Graduação em Ciências Ambientais, Brasília, 2020.As hantaviroses são zoonoses emergentes, que provocam enfermidades humanas graves, como a Síndrome Cardiopulmonar por Hantavírus (SCPH), incidente no continente americano, e a Febre Hemorrágica por Síndrome Renal (FHSR), com ocorrência na Ásia e Europa. No Brasil a SCPH é uma enfermidade de alta letalidade e tem notificação obrigatória aos serviços de saúde. O principal reservatório de SCPH são espécies de roedores generalistas, como o Necromys lasiurus, incidente no bioma do cerrado, que aumentam em abundância em paisagens nativas alteradas, podendo elevar o risco de transmissão da doença. No Distrito Federal (DF), têm surgido novos casos de SCPH em decorrência do contato dos seres com o hábitat desses roedores. Nesse contexto, a pesquisa é composta por dois artigos, no primeiro artigo, foi feita uma revisão sistêmica dos métodos utilizados para analisar a hantavirose e sua relação com o uso do solo pela metodologia Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA). O segundo artigo é a análise espacial dos locais prováveis de infecção no período de 2007 a 2017 no Sistema de Informações Geográficas (SIG) por meio do Índice Moran Global e local, Getis-Ord Gi* e pela modelagem ambiental no Dinâmica de EGO, a fim de indicar as áreas de maior risco e as variáveis ambientais que mais predispõe a doença na região do Distrito Federal. O estudo fornece informações sobre a ação de fatores da paisagem e climáticos, na incidência de hantavirose. As informações podem ser utilizadas para um melhor entendimento de como a SCPH se comporta no DF e trazer subsídios para a orientação de estratégias de monitoramento e de vigilância epidemiológica em saúde públicaHantaviruses are emerging zoonoses that cause severe human illnesses, such as Hantavirus Cardiopulmonary Syndrome (HCPS), incident in the American continent, and Hemorrhagic Fever with Renal Syndrome (HFRS) in Asia and Europe. In Brazil, HCPS is a highly lethal disease and must be treated by health services. The main cause of HCPS are species of generalist rodents, such as Necromys lasiurus, incident in the cerrado biome and increase in abundance in altered native landscapes, which may increase the risk of disease transmission. In the Federal District, new cases of HCPS emerged due to the contact of humans with the habitats of these rodents. In this context, the research consists of two articles. In the first article, a systemic review of the methods used to analyze hantavirus disease and its relationship with land use was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The second article is the spatial analysis of the probable sites of infection for the period from 2007 to 2017 in the Geographic Information System (GIS) through the Global and local Moran Index, Getis-Ord Gi * and by the environmental modeling in the EGO Dynamics. These analyses indicate the areas of greatest risk and the environmental variables that most predispose the disease in the region of the Federal District. This study provides information on the action of landscape and climatic factors on the incidence of hantavirus. The information can be used to understand better how SCPH behaves in the Federal District and provide subsidies for the guidance of monitoring strategies and epidemiological surveillance of public health

Genetic Diversity and the Spatio-Temporal Analyses of Hantaviruses in Shandong Province, China

Hemorrhagic fever with renal syndrome (HFRS) is a serious public health problem in Shandong Province, China. We conducted an epizootiologic investigation and phylogeographic and phylodynamic analyses to infer the phylogenetic relationships of hantaviruses in space and time, and gain further insights into their evolutionary dynamics in Shandong Province. Our data indicated that the Seoul virus (SEOV) is distributed throughout Shandong, whereas Hantaan virus (HTNV) co-circulates with SEOV in the eastern and southern areas of Shandong. Their distribution showed strong geographic clustering. In addition, our analyses indicated multiple evolutionary paths, long-distance transmission, and demographic expansion events for SEOV in some areas. Selection pressure analyses revealed that negative selection on hantaviruses acted as the principal evolutionary force, whereas a little evidence of positive selection exists. We found that several positively selected sites were located within major functional regions and indicated the importance of these residues for adaptive evolution of hantaviruses

Epidemic characteristics, high-risk townships and space-time clusters of human brucellosis in Shanxi Province of China, 2005–2014

BACKGROUND: Brucellosis, one of the world's most important zoonosis, has been re-emerging in China. Shanxi Province, located in northern China, where husbandry development has been accelerated in recent years, has a rather high incidence of human brucellosis but drew little attention from the researchers. This study aimed to describe the changing epidemiology of human brucellosis in Shanxi Province from 2005 to 2014 and explore high-risk towns and space-time clusters for elucidating the necessity of decentralizing disease control resource to township level in epidemic regions, particularly in hotspot areas.METHODS: We extracted data from the Chinese National Notifiable Infectious Disease Reporting System to describe the incidence and spatiotemporal distribution of human brucellosis in Shanxi Province. Geographic information system was used to identify townships at high risk for the disease. Space-Time Scan Statistic was applied to detect the space-time clusters of human brucellosis during the past decade.RESULTS: From 2005 to 2014, a total of 50,002 cases of human brucellosis were recorded in Shanxi, with a male-to-female ratio of 3.9:1. The reported incidence rate increased dramatically from 7.0/100,000 in 2005 to 23.5/100,000 in 2014, with an average annual increase of 14.5%. There were still 33.8% cases delaying diagnosis in 2014. The proportion of the affected towns increased from 31.5% in 2005 to 82.5% in 2014. High-risk towns spread from the north to the center and then south of Shanxi Province, which were basins and adjacent highlands suitable for livestock cultivation. During the past decade, there were 55 space-time clusters of human brucellosis detected in high risk towns; the clusters could happen in any season. Some clusters' location maintained stable over time.CONCLUSIONS: During the last decade, Shanxi province's human brucellosis epidemic had been aggravated and high-risk areas concentrated in some towns located in basins and adjacent highlands. Space-time clusters existed and some located steadily over time. Quite a few cases still missed timely diagnosis. Greater resources should be allocated and decentralized to mitigate the momentum of rise and improve the accessibility of prompt diagnosis treatment in the high-risk townships