Environmental risk factors and hotspot analysis of dengue distribution in Pakistan
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This study is an attempt to find out the factors responsible for sudden dengue outbreak in different cities of Pakistan during 2011. For this purpose, spatio-temporal distribution of dengue in Islamabad, Rawalpindi, Lahore, and Karachi has been taken into account. According to the available data, the factors responsible for this spread includes climate covariates like rainfall, temperature, and wind speed; social covariates like population, and area of locality, and environmental risk factors like drainage pattern and geo-hydrological conditions. Reported dengue cases from localities and Shuttle Radar Topography Mission (SRTM) 90 m digital elevation model (DEM) of study areas have been processed for hotspots, regression model and stream density in the localities of high dengue incidence. The relationship of daily dengue incidence with climate covariates during the months of July–October of the study year is analyzed. Results show that each dry spell of 2–4 days provides suitable conditions for the development and survival of dengue vectors during the wet months of July and August in the areas of high stream density and population. Very few cases have been reported in July while higher number of cases reported in the months of August, September, until late October. Hotspot analysis highlights the areas of high dengue incidence while regression analysis shows the relationship between the population and the areas of localities with the dengue incidence.
KeywordsClimate covariates Dengue outbreak Monsoon season Population Social covariates Stream density
The authors wish to thank the National Institute of Health (NIH) Islamabad, Government of the Punjab (GoP), National Institute of Populational Studies (NIPS), and Pakistan Meteorological Department (PMD) for providing the important data necessary for this manuscript.
- Climate of Pakistan (2011) Report by National Drought Monitoring Center. Pakistan Meteorological DepartmentGoogle Scholar
- Cox J, Grillet ME, Ramos OM, Amador M, Barrera R (2007) Habitat segregation of dengue vectors along an urban environmental gradient. Am J Trop Med Hyg 76:820–826Google Scholar
- Chowell G, Sanchez F (2006) Climate-based descriptive models of dengue fever. J Environ Health 68:60–63Google Scholar
- Fatima Z, Idrees M, Bajwa MA, Tahir Z, Ullah O, Zia MQ, Hussain A, Akram M, Khubaib B, Afzal S, Munir S, Saleem S, Rauff B, Badar S, Naudhani M, Butt S, Aftab M, Ali L, Ali M (2011) Serotype and genotype analysis of dengue virus by sequencing followed by phylogenetic analysis using samples from three mini outbreaks-2007–2009 in Pakistan. BMC Microbiol 10:200–203CrossRefGoogle Scholar
- Favier C, Degallier N, Dubois MA (2005) Dengue epidemic modelling: stakes and pitfalls. Asia Pac Biotechnol News 9:1191–1194Google Scholar
- Githeko AK, Lindsay SW, Confalonieri UE, Patz JA (2000) Climate change and vector-borne diseases: a regional analysis. Bull World Health Organ 78:1136–1147Google Scholar
- Jetten TH, Focks DA (1997) Potential changes in the distribution of dengue transmission under climate warming. Am J Trop Med Hyg 57:285–297Google Scholar
- World Health Organization (2012) International travel and health: situation as on 1 January 2012. World Health OrganizationGoogle Scholar
- World Health Organization (2009) Epidemiology, burden of disease and transmission. In Dengue: Guidelines for diagnosis, treatment, prevention and control. World Health Organization, Geneva, 1–21Google Scholar
- Wolff M (2002) Concepts and approaches for marine ecosystem research with reference to the tropics. Rev Biol Trop 50:395–414Google Scholar