Determination of risk factors and development of mathematical models to forecast case incidence of dengue in Gampaha District, Sri Lanka.

Abstract

ABSTRACT: Dengue is one of the most important mosquito-borne viral infection in Sri Lanka and the disease is caused by any of the four antigenically distinct Dengue Viruses (DENV). Aedes aegypti (Linnaeus) and Ae. albopictus (Skuse) are considered as vectors transmitting the virus in the country. The second highest number of dengue incidences are reported from the District of Gampaha, next to Colombo, since 2010. Overall objective of the current study was identification of risk factors, development of risk maps and prediction models for transmission of dengue and identification of efficacy of lethal ovitraps to control dengue vectors in the District of Gampaha. During the COMPONENT 1 of the study, identification of risk factors affecting transmission of dengue in selected sites in the District of Gampaha was performed. Based on epidemiological situation during the period of 2005-2014, four Medical Officer of Health (MOH) areas with highest number of dengue incidences reported, namely Kelaniya, Mahara, Negombo and Wattala, were selected as study areas. Mirigama MOH area, which had a very low level of dengue incidence, was selected as the control area. Differences in entomological indices were observed in study areas during the analysis of studied risk factors, however the study variables in high risk study areas were clustered together when compared to the control area. Broadly, socio-economic factors viz. size of the homestead, years of living in the same area, number of persons in household, monthly family income and type of premise, Entomological factors, viz. surrounding cleanliness, vegetation coverage and source of water and Knowledge, Attitude and Practices (KAP) measures, viz. waste disposal method, mosquito control measures, effects of previous dengue control projects and role of Public Health Inspector (PHI) play significant role in transmission of dengue in the high risk study areas. Transmission of DENV serotype/s and genotype/s by field-caught dengue vector mosquitoes was detected using molecular-based assays. Phylogenetic analysis of the positive mosquito pools, collected during the dengue epidemic in 2017, revealed that the causative agent for the epidemic is a migrated virus belongs to DENV-2 Cosmopolitan Clade lb strain. Under the COMPONENT 2 of the study, development of mathematical and Geographic Information System (GlS)-based models to forecast impending dengue epidemics and GIS-based risk maps to study on transmission of dengue in the District of Gampaha were performed. During mathematical modelling, rainfall, rainy days, temperature and Relative Humidity (RH) were identified as significant climatic factors affecting for the transmission of dengue. Further, number of dengue incidence in the previous month exponentially contributed to the dengue incidence in the current month. The best time series regression model developed forecasted correctly with mean absolute errors of 95.65 and 532.39 for training and validation periods, respectively. The Pierce skill score of the model was 0.49. Receiver operating characteristic of the selected model was 86% and the sensitivity was 92%. The developed random forest model forecasted dengue incidences correctly with mean absolute errors of 90.73 and 1308.56 for training and validation periods and the model demonstrated the increase of dengue incidences since March, 2017 which lead to the epidemic peak in July. GIS-based risk maps were developed to identify dengue risks in each MOH area in the district and models were developed to identify risk localities in the studied dengue high-risk areas. Positive correlations were observed with breeding containers, roads and land use during spatial correlation analysis in the high risk study areas. During COMPONENT 3 of the study, identification of dengue vector mosquito species and other mosquito species was performed. Different mosquito species were collected from the field and complete 'Folmer region' Cytochrome c Oxidase (COI) DNA barcodes were developed for 21 species of mosquitoes belong to six genera in Sri Lanka. When COI barcodes analyses utilizing distance and phylogenetic methods compared with morphological identification revealed that the mean inter-species Kimura-2-parameter pairwise divergence ranged from 7.0% to 25.4%, while that for intra-species ranged from 0.0% to 1.4%. The developed COI-based DNA barcoding approach can be used to discriminate mosquito species in the district and the study reported the presence of Culex pipiens mosquito for the first time in Sri Lanka. During COMPONENT 4 of the study, development of an Autocidal Gravid Ovitraps (AGO) with an Insect Growth Regulator (IGR) to control dengue vector mosquitoes was performed. The optimum field dosage of Novaluron in the developed Autocidal Gravid Ovitraps (AGO) was 2 ppm and the residual effect was 28 days. In the field experiments, significantly higher mortality counts of mosquito larvae were recorded in the treated area in both indoor and outdoor ovitraps. Two factor repeated measures Analysis of Variation (ANOVA) followed by the Tukey’s test confirmed that the mean mortality count is high for the developed AGOs in both indoor and outdoor settings. - Even though the mode of action of Novaluron is 100% clear, molecular docking experiments indicated that Novaluron shows greater affinity towards chitin synthase and interacts with tryptophan (try) residue at 872 position. KEYWORDS: Dengue, District of Gampaha, Phylogeny and phylogeography, Mathematical and GIS modelling, DNA barcoding, Autocidal Gravid Ovitrap, Molecular modelling