An information value based analysis of physical and climatic factors affecting dengue fever and dengue haemorrhagic fever incidence

BACKGROUND: Vector-borne diseases are the most dreaded worldwide health problems. Although many campaigns against it have been conducted, Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF) are still the major health problems of Thailand. The reported number of dengue incidences in 1998 for the Thailand was 129,954, of which Sukhothai province alone reported alarming number of 682. It was the second largest epidemic outbreak of dengue after 1987. Government arranges the remedial facilities as and when dengue is reported. But, the best way to control is to prevent it from happening. This will be possible only when knowledge about the relationship of DF/DHF with climatic and physio-environmental agents is discovered. This paper explores empirical relationship of climatic factors rainfall, temperature and humidity with the DF/DHF incidences using multivariate regression analysis. Also, a GIS based methodology is proposed in this paper to explore the influence of physio-environmental factors on dengue incidences. Remotely sensed data provided important data about physical environment and have been used for many vector borne diseases. Information Values (IV) method was utilised to derive influence of various factors in the quantitative terms. Researchers have not applied this type of analysis for dengue earlier. Sukhothai province was selected for the case study as it had high number of dengue cases in 1998 and also due to its diverse physical setting with variety of land use/land cover types. RESULTS: Preliminary results demonstrated that physical factors derived from remotely sensed data could indicate variation in physical risk factors affecting DF/DHF. A composite analysis of these three factors with dengue incidences was carried out using multivariate regression analysis. Three empirical models ER-1, ER-2 and ER-3 were evaluated. It was found that these three factors have significant relation with DF/DHF incidences and can be related to the forecast expected number of dengue cases. The results have shown significantly high coefficient of determination if applied only for the rainy season using empirical relation-2 (ER-2). These results have shown further improvement once a concept of time lag of one month was applied using the ER-3 empirical relation. ER-3 model is most suitable for the Sukhothai province in predicting possible dengue incidence with 0.81 coefficient of determination. The spatial statistical relationship of various land use/land cover classes with dengue-affected areas was quantified in the form of information value received from GIS analysis. The highest information value was obtained for the Built-up area. This indicated that Built-up area has the maximum influence on the incidence of dengue. The other classes showing negative values indicate lesser influence on dengue epidemics. Agricultural areas have yielded moderate risk areas based on their medium high information values. Water bodies have shown significant information value for DF/ DHF only in one district. Interestingly, forest had shown no influence on DF/DHF. CONCLUSION: This paper explores the potential of remotely sensed data and GIS technology to analyze the spatial factors affecting DF/DHF epidemic. Three empirical models were evaluated. It was found that Empirical Relatrion-3 (ER-3) has yielded very high coefficient of determination to forecast the number of DF/DHF incidence. An analysis of physio-environmental factors such as land use/ land cover types with dengue incidence was carried out. Influence of these factors was obtained in quantitative terms using Information Value method in the GIS environment. It was found that built-up areas have highest influence and constitute the highest risk zones. Forest areas have no influence on DF/DHF epidemic. Agricultural areas have moderate risk in DF/DHF incidences. Finally the dengue risk map of the Sukhothai province was developed using Information Value method. Dengue risk map can be used by the Public Health Department as a base map for applying preventive measures to control the dengue outbreak. Public Health Department can initiate their effort once the ER-3 predicts a possibility of significant high dengue incidence. This will help in focussing the preventive measures being applied on priority in very high and high-risk zones and help in saving time and money

Socio-Economic Resilience to Floods in Coastal Areas of Thailand

Krabi and Nakhon Si Thammarat are two coastal provinces in Thailand facing substantial threats from climate change induced hydrometeorological hazards, including enhanced coastal erosion and flooding. Human populations and livelihoods in these coastal provinces are at greater risk than those in inland provinces. However, little is known about the communities’ resilience and coping capacities regarding hydrometeorological hazards of varying magnitudes. The study conducted a quantitative socio-economic assessment of how people in Krabi and Nakhon Si Thammarat provinces manage and respond to hydrometeorological hazards, examining their resilience and coping capacities. This was a cross-sectional study based on secondary data collection on the social and economic dimensions of resilience, and a review of literature on coping mechanisms to hydrometeorological hazards within the study area. Measuring and mapping socio-economic resilience was based on the available data gathered from the social and economic dimensions, with existing or standard indicators on exposure and vulnerability applied uniformly across subdistricts. A combination of social and economic dimensions produced novel socio-economic resilience index scores by subdistrict, which were mapped accordingly for the two coastal provinces. The study also derived a coping capacity index scores by combining availability of skills or soft capacity and availability of structural resources or hard coping capacity. Socio-economic resilience index scores varied greatly amongst subdistricts. Combining the soft and hard coping capacities, the average score across districts in both provinces was 3 out of a possible 4, meaning that most of the districts were largely resilient. However, variations also existed by subdistrict. Few subdistricts in both Krabi and Nakhon Si Thammarat provinces had low coping capacity index scores between 1 and 2 out of 4. District averages of socio-economic resilience scores mask the variations at subdistrict level. More studies with rigorous methodologies at village or neighborhood level is needed to obtain a nuanced understanding of community resilience to hydrometeorological hazards

Climatic Factors Influencing Dengue Hemorrhagic Fever in Kolaka District, Indonesia

Dengue hemorrhagic fever in Indonesia is one of the serious health problems and requires understanding the occurrence of this disease. Climate Factors have a role that needs attention in the prevention of DHF disease. Understanding of disease patterns will benefit the health surveillance system and provide a way to tackle this problem. The records of dengue fever cases and climate data for the years 2010-2015 were obtained from the Health Office Kolaka District, southeast Sulawesi province and Meteorology, Climatology and Geophysics Agency in Southeast Sulawesi province, respectively. Data for the period 2010 to 2014 were used for model development through multiple linear regressions. The prediction model was used to forecast dengue cases in 2015 and the predicted results were compared with reported dengue cases in Kolaka in the past and forecasting period. Rainfall, humidity, temperature average, minimum temperature, and maximum temperature are significantly correlated with monthly cases of dengue fever. Predicted results showed a good performance where the model was able to predict 3 out of 5 epidemic outbreak events that occurred in January-March 2015 and November-December 2015. The sensitivity of detecting the outbreaks was estimated to be 60%, the specificity was 100%, positive and negative predictive value were estimated to be 100% and 77.8%, respectively. Climate has a major influence on the occurrence of dengue hemorrhagic fever infection in Kolaka district. Although the predictive model has some limitations in predicting the number of cases of monthly dengue fever, it can estimate the possibility of an outbreak three months in advance with a fairly high accuracy. The predictive model can be used to explain the incident rate of DHF of approximately 71%

Assessing Coastal Vulnerability to Climate Change: A Case Study of Nakhon Si Thammarat and Krabi

Climate change is increasingly impacting both environments and human communities. Coastal regions in Thailand are experiencing more severe impacts, which vary based on the unique physical and socio-economic characteristics of each area. To assess the vulnerability of coastal regions in Thailand, this study focused on two provinces, Nakhon Si Thammarat (NST) and Krabi, each representing distinct coastal environments. NST, situated on the Gulf of Thailand’s east coast, has an agriculture-based economy, while Krabi, on the Andaman Sea’s west coast, relies heavily on tourism. The study utilized a multi-criteria decision analysis approach (MCDA) and GIS to analyze the Coastal Vulnerability Index at the sub-district level. The results revealed that, although NST was more vulnerable than Krabi to socio-economic factors such as the poverty rate and the number of fishery households, Krabi was much more vulnerable in the physical environment, including wave height, tidal level, coastal erosion, and slope. However, overall, Krabi exhibited high to the highest levels of coastal vulnerability, while NST displayed moderate to high levels. These findings provide valuable insights for policymakers and government agencies, aiding in the development of strategies to mitigate vulnerability and enhance the quality of life for local residents in both province

The Chao Phraya delta : historical development, dynamics and challenges of Thailand's rice bowl

In Thailand, since the first epidemics in 1958, there has been a global upward trend in incidence of Dengue Hemorrhagic Fever (DHF), an acute and severe form of dengue virus infection, which remains a major public health concern. The dengue is due to an arbovirus mainly transmitted by #Aedes aegypti$, a mosquito living close to human communities. The intensity of the transmission (i.e. number of cases and speed of the spread of the disease) is dependant on the number of vectors, the serotype of the virus, the herd immunity and the environment. In the Central Plain of Thailand despite an apparent very homogenous environment (altitude, climate, type of agriculture) the incidence of DHF exhibits strong variations at the province and sub-province levels. A Geographical Information System using epidemiological data, as well as information about the land-use, demography, geography, climate has been built to identify indicators likely to help to describe areas and periods at risk for dengue transmission. A particular approach is focusing on the structure of the urban environment, the main field for dengue transmission. Different degrees and types of urbanisation appear to be linked to different intensities of dengue transmission. The main output of this study will be a method to describe areas at risk for high level of transmission and to forecast epidemic periods allowing a quick launch of dengue control activities. This study developed in the Central Plain of Thailand will be extended to other parts of the country and the same methods may be applied to similar environments in other countries where the dengue is endemic. (Résumé d'auteur

Coastal Erosion and Flood Coping Mechanisms in Southern Thailand: A Qualitative Study

Communities in coastal regions are affected by the impacts of extreme climatic events causing flooding and erosion. Reducing the impacts of flood and erosion in these areas by adopting coping strategies that fortify the resilience of individuals and their localities is desirable. This study used summative content analysis to explore the coping mechanisms of coastal communities before, during, and after various dangers relating to flooding and erosion. The findings from the study show that effective surveillance systems, disaster preparedness, risk mapping, early warning systems, availability of databases and functional command systems, as well as reliable funding are essential to efficiently cope with hazards of coastal flooding and erosion. As flooding and erosion have been predicted to be more severe due to climate change in the coming years, the adoption of effective natural and artificial mechanisms with modern technologies could help coastal regions to be more resilient in coping with the dangers associated with flooding and erosion. Pragmatic policies and programs to this end by actors are critical to averting crises induced by flooding and erosion in coastal areas

GeoHealth Thai Platform: towards a network to gather expertise, knowledge and resources in health geography

International audienceDriven by the recent awareness of the magnitude of climate and environmental changes and their impact on human health, interdisciplinary approaches are increasingly being implemented to understand health inequalities and the dynamics of diseases. Although the availability of data is growing, researchers are facing difficulties in identifying and accessing relevant data and, above all, in using these data, resulting in a paradoxically limited use of geographical information.The GeoHealth Thai Platform project aims to promote geographical and environmental approaches in the understanding of health inequalities through the use of Geographic Information Systems and Remote Sensing techniques. It proposes to address the difficulties encountered by many individual researchers by:•gathering experts and researchers together during workshops, in order to define the needs and identify the barriers to be solved; •training and providing expertise to researchers for the use of Geographic Information Systems and Remote Sensing techniques; •building an open geocatalogue to facilitate the access to spatial data.This project will be supported by a dedicated website, which will integrate the catalogue of geo-referenced data, together with online resources (documents, courses and tutorials). This poster will present the geocatalogue, at the heart of the project, as well as current and future project activities.GeoHealth Thai Platform is funded by Franco-Thai Cooperation Program in Higher Education and Research 2013-2014

Spatio-Temporal Diffusion Pattern and Hotspot Detection of Dengue in Chachoengsao Province, Thailand

In recent years, dengue has become a major international public health concern. In Thailand it is also an important concern as several dengue outbreaks were reported in last decade. This paper presents a GIS approach to analyze the spatial and temporal dynamics of dengue epidemics. The major objective of this study was to examine spatial diffusion patterns and hotspot identification for reported dengue cases. Geospatial diffusion pattern of the 2007 dengue outbreak was investigated. Map of daily cases was generated for the 153 days of the outbreak. Epidemiological data from Chachoengsao province, Thailand (reported dengue cases for the years 1999–2007) was used for this study. To analyze the dynamic space-time pattern of dengue outbreaks, all cases were positioned in space at a village level. After a general statistical analysis (by gender and age group), data was subsequently analyzed for temporal patterns and correlation with climatic data (especially rainfall), spatial patterns and cluster analysis, and spatio-temporal patterns of hotspots during epidemics. The results revealed spatial diffusion patterns during the years 1999–2007 representing spatially clustered patterns with significant differences by village. Villages on the urban fringe reported higher incidences. The space and time of the cases showed outbreak movement and spread patterns that could be related to entomologic and epidemiologic factors. The hotspots showed the spatial trend of dengue diffusion. This study presents useful information related to the dengue outbreak patterns in space and time and may help public health departments to plan strategies to control the spread of disease. The methodology is general for space-time analysis and can be applied for other infectious diseases as well

Social sciences research in neglected tropical diseases 2: A bibliographic analysis

The official published version of the article can be found at the link below.Background There are strong arguments for social science and interdisciplinary research in the neglected tropical diseases. These diseases represent a rich and dynamic interplay between vector, host, and pathogen which occurs within social, physical and biological contexts. The overwhelming sense, however, is that neglected tropical diseases research is a biomedical endeavour largely excluding the social sciences. The purpose of this review is to provide a baseline for discussing the quantum and nature of the science that is being conducted, and the extent to which the social sciences are a part of that. Methods A bibliographic analysis was conducted of neglected tropical diseases related research papers published over the past 10 years in biomedical and social sciences. The analysis had textual and bibliometric facets, and focussed on chikungunya, dengue, visceral leishmaniasis, and onchocerciasis. Results There is substantial variation in the number of publications associated with each disease. The proportion of the research that is social science based appears remarkably consistent (<4%). A textual analysis, however, reveals a degree of misclassification by the abstracting service where a surprising proportion of the "social sciences" research was pure clinical research. Much of the social sciences research also tends to be "hand maiden" research focused on the implementation of biomedical solutions. Conclusion There is little evidence that scientists pay any attention to the complex social, cultural, biological, and environmental dynamic involved in human pathogenesis. There is little investigator driven social science and a poor presence of interdisciplinary science. The research needs more sophisticated funders and priority setters who are not beguiled by uncritical biomedical promises

Spatial and temporal patterns of locally-acquired dengue transmission in Northern Queensland, Australia, 1993-2012

Background: Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992–1993. We explored spatio-temporal characteristics of locally-acquired dengue cases in northern tropical Queensland, Australia during the period 1993–2012.Methods: Locally-acquired notified cases of dengue were collected for northern tropical Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Results: 2,398 locally-acquired dengue cases were recorded in northern tropical Queensland during the study period. The areas affected by the dengue cases exhibited spatial and temporal variation over the study period. Notified cases of dengue occurred more frequently in autumn. Mapping of dengue by statistical local areas (census units) reveals the presence of substantial spatio-temporal variation over time and place. Statistically significant differences in dengue incidence rates among males and females (with more cases in females) (χ2 = 15.17, d.f. = 1, p<0.01). Differences were observed among age groups, but these were not statistically significant. There was a significant positive spatial autocorrelation of dengue incidence for the four sub-periods, with the Moran's I statistic ranging from 0.011 to 0.463 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the northern Queensland.Conclusions: Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in northern tropical Queensland, Australia. Therefore, this study provides an impetus for further investigation of clusters and risk factors in these high-risk areas