Spatiotemporal distribution of malaria and the association between its epidemic and climate factors in Hainan, China

<p>Abstract</p> <p>Background</p> <p>Hainan is one of the provinces most severely affected by malaria epidemics in China. The distribution pattern and major determinant climate factors of malaria in this region have remained obscure, making it difficult to target countermeasures for malaria surveillance and control. This study detected the spatiotemporal distribution of malaria and explored the association between malaria epidemics and climate factors in Hainan.</p> <p>Methods</p> <p>The cumulative and annual malaria incidences of each county were calculated and mapped from 1995 to 2008 to show the spatial distribution of malaria in Hainan. The annual and monthly cumulative malaria incidences of the province between 1995 and 2008 were calculated and plotted to observe the annual and seasonal fluctuation. The Cochran-Armitage trend test was employed to explore the temporal trends in the annual malaria incidences. Cross correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on malaria transmission and the auto correlation of malaria incidence. A multivariate time series analysis was conducted to construct a model of climate factors to explore the association between malaria epidemics and climate factors.</p> <p>Results</p> <p>The highest malaria incidences were mainly distributed in the central-south counties of the province. A fluctuating but distinctly declining temporal trend of annual malaria incidences was identified (Cochran-Armitage trend test <it>Z </it>= -25.14, <it>P </it>< 0.05). The peak incidence period was May to October when nearly 70% of annual malaria cases were reported. The mean temperature of the previous month, of the previous two months and the number of cases during the previous month were included in the model. The model effectively explained the association between malaria epidemics and climate factors (<it>F </it>= 85.06, <it>P </it>< 0.05, adjusted <it>R </it>²= 0.81). The autocorrelations of the fitting residuals were not significant (<it>P </it>> 0.05), indicating that the model extracted information sufficiently. There was no significant difference between the monthly predicted value and the actual value (<it>t </it>= -1.91, <it>P </it>= 0.08). The <it>R </it>²for predicting was 0.70, and the autocorrelations of the predictive residuals were not significant (<it>P </it>> 0.05), indicating that the model had a good predictive ability.</p> <p>Discussion</p> <p>Public health resource allocations should focus on the areas and months with the highest malaria risk in Hainan. Malaria epidemics can be accurately predicted by monitoring the fluctuations of the mean temperature of the previous month and of the previous two months in the area. Therefore, targeted countermeasures can be taken ahead of time, which will make malaria surveillance and control in Hainan more effective and simpler. This model was constructed using relatively long-term data and had a good fit and predictive validity, making the results more reliable than the previous report.</p> <p>Conclusions</p> <p>The spatiotemporal distribution of malaria in Hainan varied in different areas and during different years. The monthly trends in the malaria epidemics in Hainan could be predicted effectively by using the multivariate time series model. This model will make malaria surveillance simpler and the control of malaria more targeted in Hainan.</p

Combining Spatial-Temporal and Phylogenetic Analysis Approaches for Improved Understanding on Global H5N1 Transmission

Background Since late 2003, the highly pathogenic influenza A H5N1 had initiated several outbreak waves that swept across the Eurasia and Africa continents. Getting prepared for reassortment or mutation of H5N1 viruses has become a global priority. Although the spreading mechanism of H5N1 has been studied from different perspectives, its main transmission agents and spread route problems remain unsolved. Methodology/Principal Findings Based on a compilation of the time and location of global H5N1 outbreaks from November 2003 to December 2006, we report an interdisciplinary effort that combines the geospatial informatics approach with a bioinformatics approach to form an improved understanding on the transmission mechanisms of H5N1 virus. Through a spherical coordinate based analysis, which is not conventionally done in geographical analyses, we reveal obvious spatial and temporal clusters of global H5N1 cases on different scales, which we consider to be associated with two different transmission modes of H5N1 viruses. Then through an interdisciplinary study of both geographic and phylogenetic analysis, we obtain a H5N1 spreading route map. Our results provide insight on competing hypotheses as to which avian hosts are responsible for the spread of H5N1. Conclusions/Significance We found that although South China and Southeast Asia may be the virus pool of avian flu, East Siberia may be the source of the H5N1 epidemic. The concentration of migratory birds from different places increases the possibility of gene mutation. Special attention should be paid to East Siberia, Middle Siberia and South China for improved surveillance of H5N1 viruses and monitoring of migratory birds

Spatial analysis of malaria in Anhui province, China

<p>Abstract</p> <p>Background</p> <p>Malaria has re-emerged in Anhui Province, China, and this province was the most seriously affected by malaria during 2005–2006. It is necessary to understand the spatial distribution of malaria cases and to identify highly endemic areas for future public health planning and resource allocation in Anhui Province.</p> <p>Methods</p> <p>The annual average incidence at the county level was calculated using malaria cases reported between 2000 and 2006 in Anhui Province. GIS-based spatial analyses were conducted to detect spatial distribution and clustering of malaria incidence at the county level.</p> <p>Results</p> <p>The spatial distribution of malaria cases in Anhui Province from 2000 to 2006 was mapped at the county level to show crude incidence, excess hazard and spatial smoothed incidence. Spatial cluster analysis suggested 10 and 24 counties were at increased risk for malaria (<it>P </it>< 0.001) with the maximum spatial cluster sizes at < 50% and < 25% of the total population, respectively.</p> <p>Conclusion</p> <p>The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit malaria risks and to further identify environmental factors responsible for the re-emerged malaria risks. Future public health planning and resource allocation in Anhui Province should be focused on the maximum spatial cluster region.</p

Spatial analysis of hemorrhagic fever with renal syndrome in China

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is endemic in many provinces with high incidence in mainland China, although integrated intervention measures including rodent control, environment management and vaccination have been implemented for over ten years. In this study, we conducted a geographic information system (GIS)-based spatial analysis on distribution of HFRS cases for the whole country with an objective to inform priority areas for public health planning and resource allocation. METHODS: Annualized average incidence at a county level was calculated using HFRS cases reported during 1994–1998 in mainland China. GIS-based spatial analyses were conducted to detect spatial autocorrelation and clusters of HFRS incidence at the county level throughout the country. RESULTS: Spatial distribution of HFRS cases in mainland China from 1994 to 1998 was mapped at county level in the aspects of crude incidence, excess hazard and spatial smoothed incidence. The spatial distribution of HFRS cases was nonrandom and clustered with a Moran's I = 0.5044 (p = 0.001). Spatial cluster analyses suggested that 26 and 39 areas were at increased risks of HFRS (p < 0.01) with maximum spatial cluster sizes of ≤ 20% and ≤ 10% of the total population, respectively. CONCLUSION: The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit HFRS risks and to further identify environmental factors responsible for the increasing disease risks. We demonstrate a new perspective of integrating such spatial analysis tools into the epidemiologic study and risk assessment of HFRS

Genetic Variation of the Human α-2-Heremans-Schmid Glycoprotein (AHSG) Gene Associated with the Risk of SARS-CoV Infection

Genetic background may play an important role in the process of SARS-CoV infection and SARS development. We found several proteins that could interact with the nucleocapsid protein of the SARS coronavirus (SARS-CoV). α-2-Heremans-Schmid Glycoprotein (AHSG), which is required for macrophage deactivation by endogenous cations, is associated with inflammatory regulation. Cytochrome P450 Family 3A (CYP4F3A) is an ω-oxidase that inactivates Leukotriene B4 (LTB4) in human neutrophils and the liver. We investigated the association between the polymorphisms of these two inflammation-associated genes and SARS development. The linkage disequilibrium (LD) maps of these two genes were built with Haploview using data on CHB+JPT (version 2) from the HapMap. A total of ten tag SNPs were selected and genotyped. In the Guangzhou cohort study, after adjusting for age and sex, two AHSG SNPs and one CYP4F3 SNP were found to be associated with SARS susceptibility: rs2248690 (adjusted odds ratio [AOR] 2.42; 95% confidence interval [CI] 1.30-4.51); rs4917 (AOR 1.84; 95% CI 1.02-3.34); and rs3794987 (AOR 2.01; 95% CI 1.10–3.68). To further validate the association, the ten tag SNPs were genotyped in the Beijing cohort. After adjusting for age and sex, only rs2248690 (AOR, 1.63; 95% CI, 1.30–2.04) was found to be associated with SARS susceptibility. The combined analysis of the two studies confirmed tag SNP rs2248690 in AHSG as a susceptibility variant (AOR 1.70; 95% CI 1.37–2.09). The statistical analysis of the rs2248690 genotype data among the patients and healthy controls in the HCW cohort, who were all similarly exposed to the SARS virus, also supported the findings. Further, the SNP rs2248690 affected the transcriptional activity of the AHSG promoter and thus regulated the AHSG serum level. Therefore, our study has demonstrated that the AA genotype of rs2268690, which leads to a higher AHSG serum concentration, was significantly associated with protection against SARS development

Discovery of DNA Viruses in Wild-Caught Mosquitoes Using Small RNA High throughput Sequencing

BACKGROUND: Mosquito-borne infectious diseases pose a severe threat to public health in many areas of the world. Current methods for pathogen detection and surveillance are usually dependent on prior knowledge of the etiologic agents involved. Hence, efficient approaches are required for screening wild mosquito populations to detect known and unknown pathogens. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we explored the use of Next Generation Sequencing to identify viral agents in wild-caught mosquitoes. We extracted total RNA from different mosquito species from South China. Small 18-30 bp length RNA molecules were purified, reverse-transcribed into cDNA and sequenced using Illumina GAIIx instrumentation. Bioinformatic analyses to identify putative viral agents were conducted and the results confirmed by PCR. We identified a non-enveloped single-stranded DNA densovirus in the wild-caught Culex pipiens molestus mosquitoes. The majority of the viral transcripts (.>80% of the region) were covered by the small viral RNAs, with a few peaks of very high coverage obtained. The +/- strand sequence ratio of the small RNAs was approximately 7∶1, indicating that the molecules were mainly derived from the viral RNA transcripts. The small viral RNAs overlapped, enabling contig assembly of the viral genome sequence. We identified some small RNAs in the reverse repeat regions of the viral 5'- and 3' -untranslated regions where no transcripts were expected. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate for the first time that high throughput sequencing of small RNA is feasible for identifying viral agents in wild-caught mosquitoes. Our results show that it is possible to detect DNA viruses by sequencing the small RNAs obtained from insects, although the underlying mechanism of small viral RNA biogenesis is unclear. Our data and those of other researchers show that high throughput small RNA sequencing can be used for pathogen surveillance in wild mosquito vectors

The severe acute respiratory syndrome epidemic in mainland China dissected

This paper provides a review of a recently published series of studies that give a detailed and comprehensive documentation of the severe acute respiratory syndrome (SARS) epidemic in mainland China, which severely struck the country in the spring of 2003. The epidemic spanned a large geographical extent but clustered in two areas: first in Guangdong Province, and about 3 months later in Beijing with its surrounding areas. Reanalysis of all available epidemiological data resulted in a total of 5327 probable cases of SARS, of whom 343 died. The resulting case fatality ratio (CFR) of 6.4% was less than half of that in other SARS-affected countries or areas, and this difference could only partly be explained by younger age of patients and higher number of community acquired infections. Analysis of the impact of interventions demonstrated that strong political commitment and a centrally coordinated response was the most important factor to control SARS in mainland China, whereas the most stringent control measures were all initiated when the epidemic was already dying down. The long-term economic consequence of the epidemic was limited, much consumption was merely postponed, but for Beijing irrecoverable losses to the tourist sector were considerable. An important finding from a cohort study was that many former SARS patients currently suffer from avascular osteo­necrosis, as a consequence of the treatment with corticosteroids during their infection. The SARS epidemic provided valuable information and lessons relevant in controlling outbreaks of newly emerging infectious diseases, and has led to fundamental reforms of the Chinese health system. In particular, a comprehensive nation-wide internet-based disease reporting system was established

Spatial-temporal mapping and risk factors for hand foot and mouth disease in northwestern inland China.

BackgroundHand foot and mouth disease (HFMD) is becoming one of the common human infectious diseases in China. Previous studies have described HFMD in tropical or coastal areas of Asia-Pacific countries. However, limited studies have thoroughly studied the epidemiology and potential risk factors for HFMD in inland areas with complex environmental conditions.Methodology/principal findingsUsing the data from 2009 to 2018 on reported cases of Xinjiang Uighur Autonomous Region, we characterized the epidemic features of HFMD. Panel negative binomial model was used to identify climate, geographical and demographic determinants for HFMD incidence. A total of 70856 HFMD cases (average annual incidence: 305 per million persons) were reported in Xinjiang during the 10-year study period, of which 10393 (14.7%) were laboratory-confirmed and 98 (0.1%) were severe. HFMD peaked in summer every year during the study period, and incidence in 2012, 2015, 2016 and 2018 had minor peaks in autumn. After adjusting the school or holiday month, multiple factors were found to affect HFMD epidemiology: urban area being major land cover type (incidence risk ratio, IRR 2.08; 95% CI 1.50, 2.89), higher gross domestic product per capita (IRR 1.14; 95% CI 1.11, 1.16), rise in monthly average temperature (IRR 1.65; 95% CI 1.61, 1.69) and monthly accumulative precipitation (IRR 1.20; 95% CI 1.16, 1.24) predicted increase in the incidence of HFMD; farmland being major land cover type (IRR 0.72; 95% CI 0.64, 0.81), an increase of percentage of the minority (IRR 0.91; 95% CI 0.89, 0.93) and population density (IRR 0.98; 95% CI 0.98, 0.99) were related to a decrease in the incidence of HFMD.Conclusions/significanceIn conclusion, the epidemic status of HFMD in Xinjiang is characterized by low morbidity and fatality. Multiple factors have significant influences on the occurrence and transmission of HFMD in Xinjiang