Supporting local health decision making with spatial video: Dengue, Chikungunya and Zika risks in a data poor, informal community in Nicaragua

- A novel method to collect fine scale spatial data to support mosquito borne disease intervention in challenging environments.
- Spatial video can identify other disease risk factors leading to a more comprehensive disease prevention strategy.
- Standing water “hotspots” suitable for mosquito breeding are identified where intervention strategies should be targeted.
- Illegally dumped trash concentrations where health intervention strategies should be targeted are also identified.
- Spatial video also reveals behavioral factors making residents more at-risk to mosquitos and that could be targeted in local education strategies.

One challenge facing spatial scientists trying to support public health outreach and intervention in challenging environments is the lack of fine scale spatial data. These data are required to gain a better understanding of both physical and social systems; why disease occurs where it does, and how to disrupt it. While data options exist, including high resolution aerial imagery, remotely sensed data, and even online mapping products like Google Street View, these all come with limitations. One option that has previously been utilized to assess cholera risk is spatial video. Here it is used to map potential mosquito breeding sites in an endemic Dengue and Chikungunya, and emerging Zika impacted community. We show how this method can provide mapping support in the hands of non-specialist public health workers who, working in collaboration with out-of-area geographic information systems (GIS) teams, can identify where to target limited intervention resources. We use a case study of an impoverished informal style Nicaraguan community suffering from a high disease burden to show spatial variation in potential mosquito breeding habitats. A field team collected street-by-street spatial video data to produce fine scale risk maps of standing water and trash locations, which, when interpreted with the associated spatial video imagery, were used to suggest where intervention strategies should be targeted. We also discuss how these same data layers can be used to address other health concerns traditionally found in informal settlements.