Environmental factors and incidence of dengue fever and dengue haemorrhagic fever in an urban area, Southern Thailand

Using geographically weighted regression (GWR) to explore spatial varying relationships of immature mosquitoes and human densities with the incidence of dengue

The only way for dengue to spread in the human population is through the human-mosquito-human cycle. Most research in this field discusses the dengue-mosquito or dengue-human relationships over a particular study area, but few have explored the local spatial variations of dengue-mosquito and dengue-human relationships within a study area. This study examined whether spatial heterogeneity exists in these relationships. We used Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models to analyze spatial relationships and identify the geographical heterogeneities by using the information of entomology and dengue cases in the cities of Kaohsiung and Fengshan in 2002. Our findings indicate that dengue-mosquito and dengue-human relationships were significantly spatially non-stationary. This means that in some areas higher dengue incidences were associated with higher vector/host densities, but in some areas higher incidences were related to lower vector/host densities. We demonstrated that a GWR model can be used to geographically differentiate the relationships of dengue incidence with immature mosquito and human densities. This study provides more insights into spatial targeting of intervention and control programs against dengue outbreaks within the study areas.

Geographical gradient of mean age of dengue haemorrhagic fever patients in northern Thailand

Dengue haemorrhagic fever (DHF) is caused by dengue virus transmitted by Aedes mosquitoes; mean age of patients varies temporally and geographically. Variability in age of patients may be due to differences in transmission intensity or demographic structure. To compare these two hypotheses, the mean age of DHF patients from 90 districts in northern Thailand (1994-1996, 2002-2004) was regressed against (i) Aedes abundance or (ii) demographic variables (birthrate, average age) of the district. We also developed software to quantify direction and strength of geographical gradients of these variables. We found that, after adjusting for socioeconomics, climate, spatial autocorrelation, the mean age of patients was correlated only with Aedes abundance. The geographical gradient of mean age of patients originated from entomological, climate, and socioeconomic gradients. Vector abundance was a stronger determinant of mean age of patients than demographic variables, in northern Thailand.

Dengue transmission in the Asia-Pacific region: impact of climate change and socio-environmental factors

OBJECTIVE

To review the scientific evidence about the impact of climate change and socio-environmental factors on dengue transmission, particularly in the Asia-Pacific region.

METHODS

Search of the published literature on PubMed, ISI web of Knowledge and Google Scholar. Articles were included if an association between climate or socio-environmental factors and dengue transmission was assessed in any country of the Asia-Pacific region.

RESULTS

Twenty-two studies met the inclusion criteria. The weight of the evidence indicates that global climate change is likely to affect the seasonal and geographical distribution of dengue fever (DF) in the Asia-Pacific region. However, empirical evidence linking DF to climate change is inconsistent across geographical locations and absent in some countries where dengue is endemic.

CONCLUSION

Even though climate change may play an increasing role in the transmission of DF, no clear evidence shows that such impact has already occurred. More research is needed across countries to better understand the relationship between climate change and dengue transmission. Future research should also consider and adjust for the influence of important socio-environmental factors in the assessment of the climate change-related effects on dengue transmission.

Using geographic information systems and decision support systems for the prediction, prevention, and control of vector-borne diseases

Emerging and resurging vector-borne diseases cause significant morbidity and mortality, especially in the developing world. We focus on how advances in mapping, Geographic Information System, and Decision Support System technologies, and progress in spatial and space-time modeling, can be harnessed to prevent and control these diseases. Major themes, which are addressed using examples from tick-borne Lyme borreliosis; flea-borne plague; and mosquito-borne dengue, malaria, and West Nile virus disease, include (a) selection of spatial and space-time modeling techniques, (b) importance of using high-quality and biologically or epidemiologically relevant data, (c) incorporation of new technologies into operational vector and disease control programs, (d) transfer of map-based information to stakeholders, and (e) adaptation of technology solutions for use in resource-poor environments. We see great potential for the use of new technologies and approaches to more effectively target limited surveillance, prevention, and control resources and to reduce vector-borne and other infectious diseases.

Breteau Index threshold levels indicating risk for dengue transmission in areas with low Aedes infestation

We used Breteau Indices to - retrospectively - predict dengue transmission. The presence of one house block (on average about 50 houses) with a Breteau Index >or=4 in a neighbourhood (a block plus the surrounding blocks in a radius of 100 m) predicted transmission at the latter level with 81.8% sensitivity and 73.3% specificity during the first month of the Havana 2001 dengue outbreak. This result corroborates the external validity of this threshold, at least in situations with low infestations levels.

Use of mapping and spatial and space-time modeling approaches in operational control of Aedes aegypti and dengue

The aims of this review paper are to 1) provide an overview of how mapping and spatial and space-time modeling approaches have been used to date to visualize and analyze mosquito vector and epidemiologic data for dengue; and 2) discuss the potential for these approaches to be included as routine activities in operational vector and dengue control programs. Geographical information system (GIS) software are becoming more user-friendly and now are complemented by free mapping software that provide access to satellite imagery and basic feature-making tools and have the capacity to generate static maps as well as dynamic time-series maps. Our challenge is now to move beyond the research arena by transferring mapping and GIS technologies and spatial statistical analysis techniques in user-friendly packages to operational vector and dengue control programs. This will enable control programs to, for example, generate risk maps for exposure to dengue virus, develop Priority Area Classifications for vector control, and explore socioeconomic associations with dengue risk.

Geographic expansion of dengue: the impact of international travel

Dengue has emerged as an international public health problem. Reasons for the resurgence of dengue in the tropics and subtropics are complex and include unprecedented urbanization with substandard living conditions, lack of vector control, virus evolution, and international travel. Of all these factors, urbanization has probably had the most impact on the amplification of dengue within a given country, and travel has had the most impact for the spread of dengue from country to country and continent to continent. Epidemics of dengue, their seasonality, and oscillations over time are reflected by the epidemiology of dengue in travelers. Sentinel surveillance of travelers could augment existing national public health surveillance systems.