Household Dengue Vulnerability Information Model for Disseminating Vector Surveillance

Background: The mosquito perception index and habitat suitability score (MPI-HSS) can be a breakthrough for obtaining dengue transmission vulnerability information in households. Routinely observed predictor data for vector density can be used to obtain region susceptibility information. This study develops Household Vulnerability Information (HVI) and Area Susceptibility Information (ASI) models for the dissemination of Aedes vector surveillance information in the community. Methods: This is a cross-sectional study. The HVI model used the MPI-HSS indicator with data collected from 368 households in Pontianak Municipality, Kalimantan Barat, Indonesia. The ASI model used secondary data on rainfall, humidity, population density, and larva-free rate (LFA) from 2018 to 2022. Confirmatory Factor Analysis (CFA) was used for validation the MPI-HSS indicators. Logistic regression was used to determine HVI and ASI models. Results: CFA results confirm that the MPI-HSS indicator can be used to determine vector density with factor loadings ranging from 0.567 to 0.890. The HVI model from the MPI-HSS indicator has a probability score of 80.6%. The ASI can be predicted from rainfall, humidity, population density, and LFA with a probability of 0.964. Validation of the ASI model against 2022 secondary data shows a 50% match. Conclusion: The HVI model using the MPI-HSS instrument and ASI with the predictor variables can be used to disseminate information about Aedes vector surveillance. The potential dissemination of this information can be further developed using mobile apps that enable to independently input requested data for user convenience.