Comparing malaria risk exposure in rural Cambodia population using GPS tracking and questionnaires.

BACKGROUND: The Great Mekong Subregion has attained a major decline in malaria cases and fatalities over the last years, but residual transmission hotspots remain, supposedly fueled by forest workers and migrant populations. This study aimed to: (i) characterize the fine-scale mobility of forest-goers and understand links between their daily movement patterns and malaria transmission, using parasites detection via real time polymerase chain reaction (RT PCR) and the individual exposure to Anopheles bites by quantification of anti-Anopheles saliva antibodies via enzyme-linked immunosorbent assay; (ii) assess the concordance of questionnaires and Global Positioning System (GPS) data loggers for measuring mobility. METHODS: Two 28 day follow-ups during dry and rainy seasons, including a GPS tracking, questionnaires and health examinations, were performed on male forest goers representing the population at highest risk of infection. Their time spent in different land use categories and demographic data were analyzed in order to understand the risk factors driving malaria in the study area. RESULTS: Malaria risk varied with village forest cover and at a resolution of only a few kilometers: participants from villages outside the forest had the highest malaria prevalence compared to participants from forest fringe's villages. The time spent in a specific environment did not modulate the risk of malaria, in particular the time spent in forest was not associated with a higher probability to detect malaria among forest-goers. The levels of antibody response to Anopheles salivary peptide among participants were significantly higher during the rainy season, in accordance with Anopheles mosquito density variation, but was not affected by sociodemographic and mobility factors. The agreement between GPS and self-reported data was only 61.9% in reporting each kind of visited environment. CONCLUSIONS: In a context of residual malaria transmission which was mainly depicted by P. vivax asymptomatic infections, the implementation of questionnaires, GPS data-loggers and quantification of anti-saliva Anopheles antibodies on the high-risk group were not powerful enough to detect malaria risk factors associated with different mobility behaviours or time spent in various environments. The joint implementation of GPS trackers and questionnaires allowed to highlight the limitations of both methodologies and the benefits of using them together. New detection and follow-up strategies are still called for.

Pre-Pandemic Cross-Reactive Immunity against SARS-CoV-2 among Central and West African Populations.

For more than two years after the emergence of COVID-19 (Coronavirus Disease-2019), significant regional differences in morbidity persist. These differences clearly show lower incidence rates in several regions of the African and Asian continents. The work reported here aimed to test the hypothesis of a pre-pandemic natural immunity acquired by some human populations in central and western Africa, which would, therefore, pose the hypothesis of an original antigenic sin with a virus antigenically close to the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). To identify such pre-existing immunity, sera samples collected before the emergence of COVID-19 were tested to detect the presence of IgG reacting antibodies against SARS-CoV-2 proteins of major significance. Sera samples from French blood donors collected before the pandemic served as a control. The results showed a statistically significant difference of antibodies prevalence between the collected samples in Africa and the control samples collected in France. Given the novelty of our results, our next step consists in highlighting neutralizing antibodies to evaluate their potential for pre-pandemic protective acquired immunity against SARS-CoV-2. In conclusion, our results suggest that, in the investigated African sub-regions, the tested populations could have been potentially and partially pre-exposed, before the COVID-19 pandemic, to the antigens of a yet non-identified Coronaviruses.

Mobility evaluation by GPS tracking in a rural, low-income population in Cambodia.

Global Positioning System (GPS) technology is an effective tool for quantifying individuals' mobility patterns and can be used to understand their influence on infectious disease transmission. In Cambodia, mobility measurements have been limited to questionnaires, which are of limited efficacy in rural environments. In this study, we used GPS tracking to measure the daily mobility of Cambodian forest goers, a population at high risk of malaria, and developed a workflow adapted to local constraints to produce an optimal dataset representative of the participants' mobility. We provide a detailed assessment of the GPS tracking and analysis of the data, and highlight the associated difficulties to facilitate the implementation of similar studies in the future.

COVID-19: Spatial analysis of hospital case-fatality rate in France.

When the population risk factors and reporting systems are similar, the assessment of the case-fatality (or lethality) rate (ratio of cases to deaths) represents a perfect tool for analyzing, understanding and improving the overall efficiency of the health system. The objective of this article is to estimate the influence of the hospital care system on lethality in metropolitan France during the inception of the COVID-19 epidemic, by analyzing the spatial variability of the hospital case-fatality rate (CFR) between French districts. In theory, the hospital age-standardized CFR should not display significant differences between districts, since hospital lethality depends on the virulence of the pathogen (the SARS-CoV-2 virus), the vulnerability of the population (mainly age-related), the healthcare system quality, and cases and deaths definition and the recording accuracy. We analyzed hospital data on COVID-19 hospitalizations, severity (admission to intensive care units for reanimation or endotracheal intubation) and mortality, from March 19 to May 8 corresponding to the first French lockdown. All rates were age-standardized to eliminate differences in districts age structure. The results show that the higher case-fatality rates observed by districts are mostly related to the level of morbidity. Time analysis shows that the case-fatality rate has decreased over time, globally and in almost all districts, showing an improvement in the management of severe patients during the epidemic. In conclusion, it appears that during the first critical phase of COVID-19 ramping epidemic in metropolitan France, the higher case-fatality rates were generally related to the higher level of hospitalization, then potentially related to the overload of healthcare system. Also, low hospitalization with high case-fatality rates were mostly found in districts with low population density, and could due to some limitation of the local healthcare access. However, the magnitude of this increase of case-fatality rate represents less than 10 per cent of the average case-fatality rate, and this variation is small compared to much greater variation across countries reported in the literature.

Global Spread of Hemorrhagic Fever Viruses: Predicting Pandemics.

As successive epidemics have swept the world, the scientific community has quickly learned from them about the emergence and transmission of communicable diseases. Epidemics usually occur when health systems are unprepared. During an unexpected epidemic, health authorities engage in damage control, fear drives action, and the desire to understand the threat is greatest. As humanity recovers, policy-makers seek scientific expertise to improve their "preparedness" to face future events.Global spread of disease is exemplified by the spread of yellow fever from Africa to the Americas, by the spread of dengue fever through transcontinental migration of mosquitos, by the relentless influenza virus pandemics, and, most recently, by the unexpected emergence of Ebola virus, spread by motorbike and long haul carriers. Other pathogens that are remarkable for their epidemic expansions include the arenavirus hemorrhagic fevers and hantavirus diseases carried by rodents over great geographic distances and the arthropod-borne viruses (West Nile, chikungunya and Zika) enabled by ecology and vector adaptations. Did we learn from the past epidemics? Are we prepared for the worst?The ultimate goal is to develop a resilient global health infrastructure. Besides acquiring treatments, vaccines, and other preventive medicine, bio-surveillance is critical to preventing disease emergence and to counteracting its spread. So far, only the western hemisphere has a large and established monitoring system; however, diseases continue to emerge sporadically, in particular in Southeast Asia and South America, illuminating the imperfections of our surveillance. Epidemics destabilize fragile governments, ravage the most vulnerable populations, and threaten the global community.Pandemic risk calculations employ new technologies like computerized maintenance of geographical and historical datasets, Geographic Information Systems (GIS), Next Generation sequencing, and Metagenomics to trace the molecular changes in pathogens during their emergence, and mathematical models to assess risk. Predictions help to pinpoint the hot spots of emergence, the populations at risk, and the pathogens under genetic evolution. Preparedness anticipates the risks, the needs of the population, the capacities of infrastructure, the sources of emergency funding, and finally, the international partnerships needed to manage a disaster before it occurs. At present, the world is in an intermediate phase of trying to reduce health disparities despite exponential population growth, political conflicts, migration, global trade, urbanization, and major environmental changes due to global warming. For the sake of humanity, we must focus on developing the necessary capacities for health surveillance, epidemic preparedness, and pandemic response.

Does the edge effect impact on the measure of spatial accessibility to healthcare providers?

BACKGROUND: Spatial accessibility indices are increasingly applied when investigating inequalities in health. Although most studies are making mentions of potential errors caused by the edge effect, many acknowledge having neglected to consider this concern by establishing spatial analyses within a finite region, settling for hypothesizing that accessibility to facilities will be under-reported. Our study seeks to assess the effect of edge on the accuracy of defining healthcare provider access by comparing healthcare provider accessibility accounting or not for the edge effect, in a real-world application. METHODS: This study was carried out in the department of Nord, France. The statistical unit we use is the French census block known as 'IRIS' (Ilot Regroupé pour l'Information Statistique), defined by the National Institute of Statistics and Economic Studies. The geographical accessibility indicator used is the "Index of Spatial Accessibility" (ISA), based on the E2SFCA algorithm. We calculated ISA for the pregnant women population by selecting three types of healthcare providers: general practitioners, gynecologists and midwives. We compared ISA variation when accounting or not edge effect in urban and rural zones. The GIS method was then employed to determine global and local autocorrelation. Lastly, we compared the relationship between socioeconomic distress index and ISA, when accounting or not for the edge effect, to fully evaluate its impact. RESULTS: The results revealed that on average ISA when offer and demand beyond the boundary were included is slightly below ISA when not accounting for the edge effect, and we found that the IRIS value was more likely to deteriorate than improve. Moreover, edge effect impact can vary widely by health provider type. There is greater variability within the rural IRIS group than within the urban IRIS group. We found a positive correlation between socioeconomic distress variables and composite ISA. Spatial analysis results (such as Moran's spatial autocorrelation index and local indicators of spatial autocorrelation) are not really impacted. CONCLUSION: Our research has revealed minor accessibility variation when edge effect has been considered in a French context. No general statement can be set up because intensity of impact varies according to healthcare provider type, territorial organization and methodology used to measure the accessibility to healthcare. Additional researches are required in order to distinguish what findings are specific to a territory and others common to different countries. It constitute a promising direction to determine more precisely healthcare shortage areas and then to fight against social health inequalities.

Modeling spatial variation in risk of presence and insecticide resistance for malaria vectors in Laos.

Climatic, sociological and environmental conditions are known to affect the spatial distribution of malaria vectors and disease transmission. Intensive use of insecticides in the agricultural and public health sectors exerts a strong selective pressure on resistance genes in malaria vectors. Spatio-temporal models of favorable conditions for Anopheles species' presence were developed to estimate the probability of presence of malaria vectors and insecticide resistance in Lao PDR. These models were based on environmental and meteorological conditions, and demographic factors. GIS software was used to build and manage a spatial database with data collected from various geographic information providers. GIS was also used to build and run the models. Results showed that potential insecticide use and therefore the probability of resistance to insecticide is greater in the southwestern part of the country, specifically in Champasack province and where malaria incidence is already known to be high. These findings can help national authorities to implement targeted and effective vector control strategies for malaria prevention and elimination among populations most at risk. Results can also be used to focus the insecticide resistance surveillance in Anopheles mosquito populations in more restricted area, reducing the area of surveys, and making the implementation of surveillance system for Anopheles mosquito insecticide resistance possible.

Assessment of the spatial accessibility to health professionals at French census block level.

BACKGROUND: The evaluation of geographical healthcare accessibility in residential areas provides crucial information to public policy. Traditional methods - such as Physician Population Ratios (PPR) or shortest travel time - offer only a one-dimensional view of accessibility. This paper developed an improved indicator: the Index of Spatial Accessibility (ISA) to measure geographical healthcare accessibility at the smallest available infra-urban level, that is, the Îlot Regroupé pour des Indicateurs Statistiques. METHODS: This study was carried out in the department of Nord, France. Healthcare professionals are geolocalized using postal addresses available on the French state health insurance website. ISA is derived from an Enhanced Two-Step Floating Catchment Area (E2FCA). We have constructed a catchment for each healthcare provider, by taking into account residential building centroids, car travel time as calculated by Google Maps and the edge effect. Principal Component Analyses (PCA) were used to build a composite ISA to describe the global accessibility of different kinds of health professionals. RESULTS: We applied our method to studying geographical healthcare accessibility for pregnant women, by selecting three types of healthcare provider: general practitioners, gynecologists and midwives. A total of 3587 healthcare providers are potentially able to provide care for inhabitants of the department of Nord. On average there are 92 general practitioners, 22 midwives and 21 gynecologists per 100,000 residents. The composite ISA for the three types of healthcare provider is 39 per 100,000 residents. A comparative analysis between ISA and physician-population ratios indicates that ISA represents a more even distribution whereas the physician-population ratios show an 'all-or-nothing' approach. CONCLUSION: ISA is a multidimensional and improved measure, which combines the volume of services relative to population size with the proximity of services relative to the population's location, available at the smallest feasible geographical scale. It could guide policy makers towards highlighting critical areas in need of more healthcare providers, and these areas should be earmarked for further knowledge-based policy making.

Determination of Leptospira borgpetersenii serovar Javanica and Leptospira interrogans serovar Bataviae as the persistent Leptospira serovars circulating in the urban rat populations in Peninsular Malaysia.

BACKGROUND: Leptospirosis is an emerging infectious disease of global significance, and is endemic in tropical countries, including Malaysia. Over the last decade, a dramatic increase of human cases was reported; however, information on the primary vector, the rat, and the Leptospira serovars circulating among the rat population is limited. Therefore, the present study was undertaken to isolate Leptospira and characterise the serovars circulating in the urban rat populations from selected main cities in Peninsular Malaysia. METHODS: Rat trappings were carried out between October 2011 to February 2014 in five urban cities which were chosen as study sites to represent different geographical locations in Peninsular Malaysia. Microscopic agglutination test (MAT) and PCR were carried out to identify the Leptospiral serogroup and determine the pathogenic status of the isolates, respectively while pulsed-field gel electrophoresis (PFGE) and random amplified polymorphic DNA (RAPD)-PCR were used to characterize the isolates. RESULTS: Three rat species were identified from the three hundred and fifty seven rats captured with Rattus rattus, being the dominant rat species (285, 80 %) followed by Rattus norgevicus (53, 15 %) and Rattus exulans (19, 5 %). Only 39 samples (11.0 %) were positive by culture and further confirmed as pathogenic Leptospira by PCR. Significant associations were shown between host infection with locality, season, host-age and species. Based on MAT, two serogroups were identified in the population namely; L. borgpetersenii serogroup Javanica (n = 16) and L. interrogans serogroup Bataviae (n = 23). Pulsed-field gel electrophoresis (PFGE) distinguished the two serovars in the urban rat populations: L. borgpetersenii serovar Javanica (41 %), and L. interrogans serovar Bataviae (59 %). RAPD-PCR yielded 14 distinct patterns and was found to be more discriminative than PFGE. CONCLUSIONS: This study confirms two Leptospira serovars circulating among the urban rats population in Peninsular Malaysia namely; L. borgpetersenii serovar Javanica and L. interrogans serovars Bataviae. Despite the low number of isolates obtained from the rat population, this study suggests that rodent control programs and disease surveillance may help to reduce the possible risk of disease transmission.

Epidemiology of human leptospirosis in Malaysia, 2004-2012.

Leptospirosis is an emerging disease, especially in countries with a tropical climate such as Malaysia. A dramatic increase in the number of cases has been reported over the last decade; however, information on the epidemiological trends of this disease is lacking. The objective of this study is to provide an epidemiological description of human leptospirosis cases over a 9-year period (2004-2012) and disease relationship with meteorological, geographical, and demographical information. A retrospective study was undertaken to describe the patterns of human leptospirosis cases and their association with intrinsic (sex, age, and ethnicity) and extrinsic (location, rainfall, and temperature) factors. Data was grouped according to age, sex, ethnicity, seasonality and geographical distribution, and analyzed using statistical tools to understand the influence of all the different factors on disease incidence. A total of 12,325 cases of leptospirosis were reported between 2004 and 2012 with an upward trend in disease incidence, with the highest in 2012. Three hundred thirty-eight deaths were reported with an overall case fatality rate of 2.74%, with higher incidence in males (9696; 78.7%) compared with female patients (2629; 21.3%), and overall male to female ratio of 3.69:1. Patients aged cohorts between 30-39 years old (16.22 per 100,000 population) had the highest disease incidence while the lowest incidence occurred between <1 to 9 years old (3.44 per 100,000 population). The average incidence was highest amongst Malays (10.97 per 100,000 population), followed by Indians (7.95 per 100,000 population). Stratification according to geographical distribution showed that the state of Malacca had the highest average disease incidence (11.12 per 100,000 population) followed by Pahang (10.08 per 100,000 population). The states of Terengganu, Kelantan, and Perak recorded similar rates of incidence (≈8.00 per 100,000 population), while Johor with the least number of reported cases (1.80 per 100,000 population). Positive relationships were recorded between the number of reported cases with the number of raining days per month and monthly average temperature (p-value<0.05). However, no significant association was noted between rainfall volume and number of reported Leptospirosis cases. This collaborative efforts between medical, academic and governmental institutions has enabled the construction of this comprehensive database that is essential to understand the disease trends in Malaysia and add insights into the prevention and control of this disease.

Spatial Pattern Detection of Tuberculosis: A Case Study of Si Sa Ket Province, Thailand.

This retrospective population-based study was conducted to analyze spatial patterns of tuberculosis (TB) incidence in Si Sa Ket province, Thailand. TB notification data from 2004 to 2008 collected from TB clinics throughout the province was used along with population data to reveal a descriptive epidemiology of TB incidences. Global clustering patterns of the occurrence were assessed by using global spatial autocorrelation techniques. Additionally, local spatial pattern detection was performed by using local spatial autocorrelation and spatial scan statistic methods. The findings indicated clusters of the disease occurred in the study area. More specifically, significantly high-rate clusters were mostly detected in Mueang Si Sa Ket and Khukhan districts, which are located in the northwestern part of the province, while significantly low-rate clusters were persistent in Kantharalak and Benchalak districts, which are located at the southeastern area.

Understanding the emergence of ebola virus disease in sierra leone: stalking the virus in the threatening wake of emergence.

Since Ebola Virus Disease (EVD) was first identified in 1976 in what is now the Democratic Republic of Congo, and despite the numerous outbreaks recorded to date, rarely has an epidemic origin been identified. Indeed, among the twenty-one most documented EVD outbreaks in Africa, an index case has been identified four times, and hypothesized in only two other instances. The initial steps of emergence and spread of a virus are critical in the development of a potential outbreak and need to be thoroughly dissected and understood in order to improve on preventative strategies. In the current West African outbreak of EVD, a unique index case has been identified, pinpointing the geographical origin of the epidemic in Guinea. Herein, we provide an accounting of events that serve as the footprint of EVD emergence in Sierra Leone and a road map for risk mitigation fueled by lessons learned.

Long-term persistence of Chikungunya virus neutralizing antibodies in human populations of North Eastern Thailand.

BACKGROUND: Chikungunya virus (CHIKV) outbreak recurrences in Thailand are unpredictable and separated by unexplained and often long silent epidemiological periods that can last for several years. These silent periods could be explained in part by the fact that infection with one CHIKV strain confers lasting natural immunity, even against other CHIKV strains. In this study we evaluated the persistence of CHIKV-specific neutralizing antibodies in the population of Chumpae District, Khon Kaen Province, nineteen years after a CHIKV outbreak occurred in the same area in 1991. FINDINGS: Overall 39% (44/111) of 111 former patients had neutralizing antibodies reacting against CHIKV ECSA strain. Consistently high titers of neutralizing antibodies were found in 75% (33/44) of all positively-reacting sera, 70% of which (23/33) were collected from individuals amongst the >60 years old age group. Although the prevalence found in Pong Haeng village (70%) was significantly higher than the prevalence detected in the Nong Thum village (14%), control study villages without known previous Chikungunya epidemics had a high Chikungunya neutralizing antibody prevalence (65%). CONCLUSIONS: More than one-third of the pre-exposed population had persisting natural immunity that was more likely boosted by recent and repetitive exposure to the emerging ECSA CHIKV in Thailand. Also, Chikungunya virus appears to largely circulate in the country with a great variability appears between villages or area probably associated with the vector abundance and efficiency. Altogether these results show a potential for a lifelong immunity against CHIKV. Given the rapid spread of the highly pathogenic ECSA strain in Southern Thailand, the development of CHIK vaccine is strongly recommended.

Poultry farm vulnerability and risk of avian influenza re-emergence in Thailand.

Highly pathogenic avian influenza (HPAI) remains of concern as a major potential global threat. This article evaluates and discusses the level of vulnerability of medium and small-scale commercial poultry production systems in Thailand related to avian influenza virus re-emergence. We developed a survey on 173 farms in Nakhon Pathom province to identify the global level of vulnerability of farms, and to determine which type of farms appears to be more vulnerable. We used official regulations (the Good Agricultural Practices and Livestock Farm Standards regulations) as a reference to check whether these regulations are respected. The results show that numerous vulnerability factors subsist and could represent, in case of HPAI re-emergence, a significant risk for a large spread of the disease. Bio-security, farm management and agro-commercial practices are particularly significant on that matter: results show that these practices still need a thorough improvement on a majority of farms. Farms producing eggs (especially duck eggs) are more vulnerable than farms producing meat. Those results are consistent with the type of farms that were mostly affected during the 2004-2008 outbreaks in Thailand.

Mapping urban and peri-urban breeding habitats of Aedes mosquitoes using a fuzzy analytical hierarchical process based on climatic and physical parameters.

The spread of dengue fever depends mainly on the availability of favourable breeding sites for its mosquito vectors around human dwellings. To investigate if the various factors influencing breeding habitats can be mapped from space, dengue indices, such as the container index, the house index and the Breteau index, were calculated from Ministry of Public health data collected three times annually in Phitsanulok, Thailand between 2009 and 2011. The most influential factors were found to be temperature, humidity, rainfall, population density, elevation and land cover. Models were worked out using parameters mostly derived from freely available satellite images and fuzzy logic software with parameter synchronisation and a predication algorithm based on data mining and the Decision Tree method. The models developed were found to be sufficiently flexible to accommodate additional parameters and sampling data that might improve prediction of favourable breeding hotspots. The algorithm applied can not only be used for the prediction of near real-time scenarios with respect to dengue, but can also be applied for monitoring other diseases influenced by environmental and climatic factors. The multi-criteria model presented is a cost-effective way of identifying outbreak hotspots and early warning systems lend themselves for development based on this strategy. The proposed approach demonstrates the successful utilisation of remotely sensed images to map mosquito breeding habitats.

Dengue, Japanese encephalitis and Chikungunya virus antibody prevalence among captive monkey (Macaca nemestrina) colonies of Northern Thailand.

The potential of macaque Macaca nemestrina leonina in Thailand to be infected by endemic arboviruses was assessed. The prevalence of antibodies of three arboviruses actively circulating in Thailand was determined by Plaque Reduction Neutralization assay procedures using samples from captive colonies in Northern Thailand. Out of 38 macaques, 9 (24%) presented reacting antibodies against dengue virus, 5 (13%) against Japanese encephalitis virus, and 4 (10%) against Chikungunya virus. Our results indicate that the northern pig-tailed macaque in Thailand can be infected by these arboviruses, inferring therefore that their virus specific vectors have bitten them. Given that, northern pig-tailed macaque represents an abundant population, living in close range to human or in peridomestic setting, they could play a role as potential reservoir host for arboviruses circulating in Thailand.

Spatial diffusion of influenza outbreak-related climate factors in Chiang Mai Province, Thailand.

Influenza is one of the most important leading causes of respiratory illness in the countries located in the tropical areas of South East Asia and Thailand. In this study the climate factors associated with influenza incidence in Chiang Mai Province, Northern Thailand, were investigated. Identification of factors responsible for influenza outbreaks and the mapping of potential risk areas in Chiang Mai are long overdue. This work examines the association between yearly climate patterns between 2001 and 2008 and influenza outbreaks in the Chiang Mai Province. The climatic factors included the amount of rainfall, percent of rainy days, relative humidity, maximum, minimum temperatures and temperature difference. The study develops a statistical analysis to quantitatively assess the relationship between climate and influenza outbreaks and then evaluate its suitability for predicting influenza outbreaks. A multiple linear regression technique was used to fit the statistical model. The Inverse Distance Weighted (IDW) interpolation and Geographic Information System (GIS) techniques were used in mapping the spatial diffusion of influenza risk zones. The results show that there is a significance correlation between influenza outbreaks and climate factors for the majority of the studied area. A statistical analysis was conducted to assess the validity of the model comparing model outputs and actual outbreaks.

Analyzing the spatio-temporal relationship between dengue vector larval density and land-use using factor analysis and spatial ring mapping.

BACKGROUND: Dengue, a mosquito-borne febrile viral disease, is found in tropical and sub-tropical regions and is now extending its range to temperate regions. The spread of the dengue viruses mainly depends on vector population (Aedes aegypti and Aedes albopictus), which is influenced by changing climatic conditions and various land-use/land-cover types. Spatial display of the relationship between dengue vector density and land-cover types is required to describe a near-future viral outbreak scenario. This study is aimed at exploring how land-cover types are linked to the behavior of dengue-transmitting mosquitoes. METHODS: Surveys were conducted in 92 villages of Phitsanulok Province Thailand. The sampling was conducted on three separate occasions in the months of March, May and July. Dengue indices, i.e. container index (C.I.), house index (H.I.) and Breteau index (B.I.) were used to map habitats conducible to dengue vector growth. Spatial epidemiological analysis using Bivariate Pearson's correlation was conducted to evaluate the level of interdependence between larval density and land-use types. Factor analysis using principal component analysis (PCA) with varimax rotation was performed to ascertain the variance among land-use types. Furthermore, spatial ring method was used as to visualize spatially referenced, multivariate and temporal data in single information graphic. RESULTS: Results of dengue indices showed that the settlements around gasoline stations/workshops, in the vicinity of marsh/swamp and rice paddy appeared to be favorable habitat for dengue vector propagation at highly significant and positive correlation (p = 0.001) in the month of May. Settlements around the institutional areas were highly significant and positively correlated (p = 0.01) with H.I. in the month of March. Moreover, dengue indices in the month of March showed a significant and positive correlation (p <= 0.05) with deciduous forest. The H.I. of people living around horticulture land were significantly and positively correlated (p = 0.05) during the month of May, and perennial vegetation showed a highly significant and positive correlation (p = 0.001) in the month of March with C.I. and significant and positive correlation (p <= 0.05) with B.I., respectively. CONCLUSIONS: The study concluded that gasoline stations/workshops, rice paddy, marsh/swamp and deciduous forests played highly significant role in dengue vector growth. Thus, the spatio-temporal relationships of dengue vector larval density and land-use types may help to predict favorable dengue habitat, and thereby enables public healthcare managers to take precautionary measures to prevent impending dengue outbreak.

Risk factors for Zaire ebolavirus--specific IgG in rural Gabonese populations.

BACKGROUND: In Gabon, several Ebolavirus outbreaks have occurred exclusively in the northeastern region. We conducted a large serosurvey to identify areas and populations at risk and potential demographic, clinical, and behavioral risk factors. METHODS: Blood samples and clinical and sociodemographic data were collected from 4349 adults and 362 children in a random sample of 220 villages in the 9 provinces of Gabon. An enzyme-linked immunosorbent assay was used to detect Zaire ebolavirus (ZEBOV)-specific IgG, and thin blood smears were used to detect parasites. Logistic regression was implemented using Stata software (Stata), and a probability level of <.05 was considered to be statistically significant. RESULTS: The prevalence of ZEBOV-specific IgG was 15.3% overall, increasing to 32.4% (P< .001) in forest areas. No sociodemographic risk factors were found, but the antibody prevalence increased linearly up to 20 years of age. Chronic arthralgia and amicrofilaremia were the only factors associated with ZEBOV seropositivity. CONCLUSIONS: These findings confirm the endemicity of ZEBOV in Gabon and its link to the ecosystem. Human antibody positivity would appear to be to the result of exposure to contaminated fruits.

Epidemiologic relationship between Toscana virus infection and Leishmania infantum due to common exposure to Phlebotomus perniciosus sandfly vector.

Sand flies are recognised vectors of parasites in the genus Leishmania and a number of arthropod-borne viruses, in particular viruses within the genus Phlebovirus, family Bunyaviridae. In southern France, Toscana phlebovirus (TOSV) is recognized as a prominent cause of summer meningitis. Since Leishmania and TOSV have a common vector (Phlebotomus perniciosus), an epidemiologic link has been assumed for a long time. However, there is no scientific evidence of such a link between human leishmaniosis and phleboviral infections. To identify a possible link, we investigated the presence and distribution of antibodies against these two microorganisms (i) in individuals and (ii) at a spatial level in the city of Marseille (south-eastern France). Five hundred sera were selected randomly in the biobank of the Department of Parasitology of the Public Hospitals of Marseille. All sera were previously tested for IgG against Leishmania by Western Blotting, and TOSV IgG were detected by indirect immunofluorescence. The seropositivity rates were 21.4% for TOSV and 28% for Leishmania. Statistical analysis demonstrated that seropositivity for one pathogen was significantly associated with seropositivity to the other pathogen. This result provided the first robust evidence for the existence of an epidemiological relationship between Leishmania infantum and TOSV. Addresses of tested patients were geolocalized and integrated into Geographical Information System software, in order to test spatial relationship between the two pathogens. Spatial analysis did not allow to identify (i) specific patterns for the spatial distribution of positive serological results for TOSV or Leishmania, and (ii) a spatial relationship between Leishmania and TOSV positive serological results. This may reflect the fact that the sample studied was not powerful enough to demonstrate either a spatial clustering or co-location, i.e. that the actual risk exposure area is smaller than the mean of distance between patients in our study (245 m).