Multivariate spatio-temporal approach to identify vulnerable localities in dengue risk areas using Geographic Information System (GIS).

Dengue is one of the most important vector-borne infection in Sri Lanka currently leading to vast economic and social burden. Neither a vaccine nor drug is still not being practiced, vector controlling is the best approach to control disease transmission in the country. Therefore, early warning systems are imminent requirement.

Entomological surveillance with viral tracking demonstrates a migrated viral strain caused dengue epidemic in July, 2017 in Sri Lanka.

Dengue is the most important mosquito-borne viral infection disease in Sri Lanka triggering extensive economic and social burden in the country. Even after numerous source reduction programmes, more than 30,000 incidences are reporting in the country every year. The last and greatest dengue epidemic in the country was reported in July, 2017 with more than 300 dengue related deaths and the highest number of dengue incidences were reported from the District of Gampaha.

Use of Novaluron-Based Autocidal Gravid Ovitraps to Control Dengue Vector Mosquitoes in the District of Gampaha, Sri Lanka.

Dengue is the most important mosquito-borne viral infection in Sri Lanka causing an enormous social and economic burden in the country. In the absence of therapeutic drugs and the developed vaccines are under investigation, vector control is the best strategy to reduce the disease transmission. Therefore, the development of novel tools to control dengue vector mosquitoes has become the need of the hour.

A forecasting model for dengue incidence in the District of Gampaha, Sri Lanka.

Background: Dengue is one of the major health problems in Sri Lanka causing an enormous social and economic burden to the country. An accurate early warning system can enhance the efficiency of preventive measures. The aim of the study was to develop and validate a simple accurate forecasting model for the District of Gampaha, Sri Lanka.