The aim of the present study was to identify geographical areas and time periods of potential clusters of dengue cases based on ecological, socio-economic and demographic factors in northern Sri Lanka from January 2010 to December 2013. Remote sensing (RS) was used to develop an index comprising rainfall, humidity and temperature data. Remote sensing data gathered by the AVNIR-2 instrument onboard the ALOS satellite were used to detect urbanisation, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analysed RS data and databases were integrated into a geographical information system (GIS) enabling space-time clustering analysis. Our results indicate that increases in the number of combinations of ecological, socio-economic and demographic factors that are present or above the average contribute to significantly high rates of space-time dengue clusters. The spatio-temporal association that consolidates the two kinds of associations into one can ensure a more stable model for forecasting. An integrated spatiotemporal prediction model at a smaller level using ecological, socioeconomic and demographic factors could lead to substantial improvements in dengue control and prevention by allocating the right resources to the appropriate places at the right time.

Provision of field antenatal clinics, early entry to ANC, and domiciliary care by PHM need improvement.

Objective To assess the prevalence of risk conditions among antenatal women in the Vavuniya District.Design and setting A cross-sectional study was conducted among 392 pregnant women who had completed 36 weeks of gestation and were admitted or referred to two leading hospitals in the district.Measurements Women were interviewed consecutively using a questionnaire, and their antenatal details were extracted from records by trained investigators. Data on socio-demographics, antenatal care utilisation, risk condition in present and past pregnancies, and preexisting illnesses were obtained.

ABSTRACT:Dengue outbreaks are affected by biological, ecological, socio-economic and demographic factors that vary over time and space. These factors have been examined separately, with limited success, and still require clarification. The present study aimed to investigate the spatial and temporal relationships between these factors and dengue outbreaks in the northern region of Sri Lanka.Remote sensing (RS) data gathered from a plurality of satellites: TRMM TMI, Aqua AMSR-E, GCOM-W AMSR2, DMSP SSM/I, DMSP SSMIS, NOAA-19 AMSU, MetOp-A AMSU and GEO IR were used to develop an index comprising rainfall. Humidity (total precipitable water, or vertically integrated water vapor amount) and temperature (surface temperature) data were acquired from the JAXA Satellite Monitoring for Environmental Studies (JASMES) portal which were retrieved and processed from the Aqua/MODIS and Terra/MODIS data. RS data gathered by ALOS/AVNIR-2 were used to detect urbanization, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analyzed RS data and databases were integrated into geographic information systems, enabling both spatial association analysis and spatial statistical analysis. Our findings show that the combination of ecological factors derived from RS data and socio-economic and demographic factors is suitable for predicting spatial and temporal patterns of dengue outbreaks.

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