114 research outputs found

    Spatial heterogeneity of parasite co-infection: Determinants and geostatistical prediction at regional scales.

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    Multiple parasite infections are widespread in the developing world and understanding their geographical distribution is important for spatial targeting of differing intervention packages. We investigated the spatial epidemiology of mono- and co-infection with helminth parasites in East Africa and developed a geostatistical model to predict infection risk. The data used for the analysis were taken from standardised school surveys of Schistosoma mansoni and hookworm (Ancylostoma duodenale/Necator americanus) carried out between 1999 and 2005 in East Africa. Prevalence of mono- and co-infection was modelled using satellite-derived environmental and demographic variables as potential predictors. A Bayesian multi-nominal geostatistical model was developed for each infection category for producing maps of predicted co-infection risk. We show that heterogeneities in co-infection with S. mansoni and hookworm are influenced primarily by the distribution of S. mansoni, rather than the distribution of hookworm, and that temperature, elevation and distance to large water bodies are reliable predictors of the spatial large-scale distribution of co-infection. On the basis of these results, we developed a validated geostatistical model of the distribution of co-infection at a scale that is relevant for planning regional disease control efforts that simultaneously target multiple parasite species

    The epidemiology of Plasmodium vivax and Plasmodium falciparum malaria in China, 2004-2012: from intensified control to elimination

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    BackgroundIn China, the national malaria elimination programme has been operating since 2010. This study aimed to explore the epidemiological changes in patterns of malaria in China from intensified control to elimination stages.MethodsData on nationwide malaria cases from 2004 to 2012 were extracted from the Chinese national malaria surveillance system. The secular trend, gender and age features, seasonality, and spatial distribution by Plasmodium species were analysed.ResultsIn total, 238,443 malaria cases were reported, and the proportion of Plasmodium falciparum increased drastically from <10% before 2010 to 55.2% in 2012. From 2004 to 2006, malaria showed a significantly increasing trend and with the highest incidence peak in 2006 (4.6/100,000), while from 2007 onwards, malaria decreased sharply to only 0.18/100,000 in 2012. Males and young age groups became the predominantly affected population. The areas affected by Plasmodium vivax malaria shrunk, while areas affected by P. falciparum malaria expanded from 294 counties in 2004 to 600 counties in 2012.ConclusionsThis study demonstrated that malaria has decreased dramatically in the last five years, especially since the Chinese government launched a malaria elimination programme in 2010, and areas with reported falciparum malaria cases have expanded over recent years. These findings suggest that elimination efforts should be improved to meet these changes, so as to achieve the nationwide malaria elimination goal in China in 2020

    The Case for Mass Treatment of Intestinal Helminths in Endemic Areas.

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    Two articles published earlier this year in the International Journal of Epidemiology [1,2] have re-ignited the debate over the World Health Organization's long-held recommendation of mass-treatment of intestinal helminths in endemic areas. In this note, we discuss the content and relevance of these articles to the policy debate, and review the broader research literature on the educational and economic impacts of deworming. We conclude that existing evidence still indicates that mass deworming is a cost-effective health investment for governments in low-income countries where worm infections are widespread

    Spatial analysis of community-onset Staphylococcus aureus bacteremia in Queensland, Australia

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    Objectives. To investigate and describe the relationship between indigenous Australian populations, residential aged care services, and community-onset Staphylococcus aureus bacteremia (SAB) among patients admitted to public hospitals in Queensland, Australia. Design. Ecological study. Methods. We used administrative healthcare data linked to microbiology results from patients with SAB admitted to Queensland public hospitals from 2005 through 2010 to identify community-onset infections. Data about indigenous Australian population and residential aged care services at the local government area level were obtained from the Queensland Office of Economic and Statistical Research. Associations between community-onset SAB and indigenous Australian population and residential aged care services were calculated using Poisson regression models in a Bayesian framework. Choropleth maps were used to describe the spatial patterns of SAB risk. Results. We observed a 21% increase in relative risk (RR) of bacteremia with methicillin-susceptible S. aureus (MSSA; RR, 1.21 [95% credible interval, 1.15-1.26]) and a 24% increase in RR with nonmultiresistant methicillin-resistant S. aureus (nmMRSA; RR, 1.24 [95% credible interval, 1.13-1.34]) with a 10% increase in the indigenous Australian population proportion. There was no significant association between RR of SAB and the number of residential aged care services. Areas with the highest RR for nmMRSA and MSSA bacteremia were identified in the northern and western regions of Queensland. Conclusions. The RR of community-onset SAB varied spatially across Queensland. There was increased RR of community-onset SAB with nmMRSA and MSSA in areas of Queensland with increased indigenous population proportions. Additional research should be undertaken to understand other factors that increase the risk of infection due to this organism

    A mathematical model of Chikungunya dynamics and control: the major epidemic on Reunion Island

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    Chikungunya is a re-emerging arboviral disease transmitted by Aedes spp. mosquitoes. Although principally endemic to Africa and Asia, recent outbreaks have occurred in Europe following introductions by returning travellers. A particularly large outbreak occurred on Réunion Island in 2006, the published data from which forms the basis of the current study. A simple, deterministic mathematical model of the transmission of the virus between humans and mosquitoes was constructed and parameterised with the up-to-date literature on infection biology. The model is fitted to the large Réunion epidemic, resulting in an estimate of 4.1 for the type reproduction number of chikungunya. Although simplistic, the model provided a close approximation of both the peak incidence of the outbreak and the final epidemic size. Sensitivity analysis using Monte Carlo simulation demonstrated the strong influence that both the latent period of infection in humans and the pre-patent period have on these two epidemiological outcomes. We show why separating these variables, which are epidemiologically distinct in chikungunya infections, is not only necessary for accurate model fitting but also important in informing control

    A high-resolution geospatial surveillance-response system for malaria elimination in Solomon Islands and Vanuatu

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    A high-resolution surveillance-response system has been developed within a geographic information system (GIS) to support malaria elimination in the Pacific. This paper examines the application of a GIS-based spatial decision support system (SDSS) to automatically locate and map the distribution of confirmed malaria cases, rapidly classify active transmission foci, and guide targeted responses in elimination zones.; Customized SDSS-based surveillance-response systems were developed in the three elimination provinces of Isabel and Temotu, Solomon Islands and Tafea, Vanuatu. Confirmed malaria cases were reported to provincial malaria offices upon diagnosis and updated into the respective SDSS as part of routine operations throughout 2011. Cases were automatically mapped by household within the SDSS using existing geographical reconnaissance (GR) data. GIS queries were integrated into the SDSS-framework to automatically classify and map transmission foci based on the spatiotemporal distribution of cases, highlight current areas of interest (AOI) regions to conduct foci-specific targeted response, and extract supporting household and population data. GIS simulations were run to detect AOIs triggered throughout 2011 in each elimination province and conduct a sensitivity analysis to calculate the proportion of positive cases, households and population highlighted in AOI regions of a varying geographic radius.; A total of 183 confirmed cases were reported and mapped using the SDSS throughout 2011 and used to describe transmission within a target population of 90,354. Automatic AOI regions were also generated within each provincial SDSS identifying geographic areas to conduct response. 82.5% of confirmed cases were automatically geo-referenced and mapped at the household level, with 100% of remaining cases geo-referenced at a village level. Data from the AOI analysis indicated different stages of progress in each province, highlighting operational implications with regards to strategies for implementing surveillance-response in consideration of the spatiotemporal nature of cases as well as logistical and financial constraints of the respective programmes.; Geospatial systems developed to guide Pacific Island malaria elimination demonstrate the application of a high resolution SDSS-based approach to support key elements of surveillance-response including understanding epidemiological variation within target areas, implementing appropriate foci-specific targeted response, and consideration of logistical constraints and costs

    Impact of “Grain to Green” programme on echinococcosis infection in Ningxia Hui Autonomous Region of China

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    Cystic echinococcosis (CE) is endemic among the human population of Xiji County, Ningxia Hui Autonomous Region, China, where the prevalence is estimated to be between 2.2% and 3.6%. Government-run sheep abattoirs in Xiji County have closed in recent years and, as a consequence, slaughter is carried out mostly at rural market places. The market place in Xinglong Township, Xiji County, is home to an increasing number of stray dogs and the lack of government control over slaughter practices potentially favours Echinococcus granulosus transmission. A survey of sheep, goats and cattle reared in Xiji County was conducted in Xinglong Market and Xinglong Township to determine prevalence and transmission dynamics of E. granulosus infection. The liver and lungs of all livestock aged one year and older were examined macroscopically post mortem; visual examination and palpation of organs determined overall prevalence of E. granulosus. Cysts consistent in appearance with E. granulosus were observed in 2/184 sheep (prevalence 1.0%) and 1/55 of the cattle examined (prevalence 1.8%); 0/13 goats were found to be infected. However, microscopic examination of these suspected cysts failed to confirm these samples as E. granulosus, giving a prevalence of confirmed infection of zero percent in all three species. The prevalence of liver fluke was 61.3% in sheep and 12.7% in cattle with a significant difference between males and females (

    Spatial and temporal patterns of diarrhoea in Bhutan 2003–2013

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    Abstract Background To describe spatiotemporal patterns of diarrhoea in Bhutan, and quantify the association between climatic factors and the distribution and dynamics of the disease. Methods Nationwide data on diarrhoea were obtained for 2003 to 2013 from the Health Information and Management System (HIMS), Ministry of Health, Bhutan. Climatic variables were obtained from the Department of Hydro Met Services, Ministry of Economic Affairs, Bhutan. Seasonal trend decomposition was used to examine secular trends and seasonal patterns of diarrhoea. A Bayesian conditional autoregressive (CAR) model was used to quantify the relationship between monthly diarrhoea, maximum temperature, rainfall, age and gender. Results The monthly average diarrhoea incidence was highly seasonal. Diarrhoea incidence increased by 0.6% (95% CrI: 0.5–0.6%) for every degree increase in maximum temperature; and 5% (95 Cr I: 4.9–5.1%) for a 1 mm increase in rainfall. Children aged <5 years were found to be 74.2% (95% CrI: 74.1–74.4) more likely to experience diarrhoea than children and adults aged ≥5 years and females were 4.9% (95% CrI: 4.4–5.3%) less likely to suffer from diarrhoea as compared to males. Significant residual spatial clustering was found after accounting for climate and demographic variables. Conclusions Diarrhoea incidence was highly seasonal, with positive associations with maximum temperature and rainfall and negative associations with age and being female. This calls for public health actions to reduce future risks of climate change with great consideration of local climatic conditions. In addition, protection of <5 years children should be prioritize through provision of rotavirus vaccination, safe and clean drinking water, and proper latrines

    Ending Malaria Transmission in the Asia Pacific Malaria Elimination Network (APMEN) Countries: Challenges and the Way Forward

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    Member countries in the Asia Pacific Malaria Elimination Network (APMEN) are pursuing the global goal of malaria elimination by 2030. Different countries are in various phases of malaria elimination and this review aims to present a compilation of available evidence on the challenges and way forward for malaria elimination in APMEN countries. Malaria transmission in these States is complex. APMEN member countries include the largest populations living in areas of malaria transmission risk outside Africa. They are a global source for spread of artemisinin-based combination therapy (ACT) resistance, include the biggest burden of Plasmodium vivax and zoonotic malaria, and face many geopolitical and socio-economic factors that will challenge malaria elimination efforts. These challenges can be addressed in part through operational research to identify country-specific solutions, making better use of operational data such as through spatial decision support system (SDSS) approaches, strengthening surveillance, and cross-border initiative for coordinated action
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