Use of trained scent dogs for detection of COVID-19 and evidence of cost-saving.

Background: One of the lessons learned from the coronavirus disease 2019 (COVID-19) pandemic is the importance of early, flexible, and rapidly deployable disease detection methods. Currently, diagnosis of COVID-19 requires the collection of oro/nasopharyngal swabs, nasal turbinate, anterior nares and saliva but as the pandemic continues, disease detection methods that can identify infected individuals earlier and more quickly will be crucial for slowing the spread of the virus. Previous studies have indicated that dogs can be trained to identify volatile organic compounds (VOCs) produced during respiratory infections.

Citizen science for monitoring the spatial and temporal dynamics of malaria vectors in relation to environmental risk factors in Ruhuha, Rwanda.

Background: As part of malaria prevention and control efforts, the distribution and density of malaria mosquitoes requires continuous monitoring. Resources for long-term surveillance of malaria vectors, however, are often limited. The aim of the research was to evaluate the value of citizen science in providing insight into potential malaria vector hotspots and other malaria relevant information, and to determine predictors of malaria vector abundance in a region where routine mosquito monitoring has not been established to support vector surveillance.

Monitoring mosquito nuisance for the development of a citizen science approach for malaria vector surveillance in Rwanda.

Background: Many countries, including Rwanda, have mosquito monitoring programmes in place to support decision making in the fight against malaria. However, these programmes can be costly, and require technical (entomological) expertise. Involving citizens in data collection can greatly support such activities, but this has not yet been thoroughly investigated in a rural African context.