Mosqlimate
For 40 years, Brazil has witnessed the emergence of diseases transmitted by the mosquito Aedes aegypti: DENV-1 (1986), DENV-2 (1991), DENV-3 (2001), DENV-4 (2010), Chikungunya (2014), and Zika (2015), with severe human and economic costs. Viruses at risk of emergence are Nhong-nhong, Mayaro, and Oropouche. Misdiagnosis is common, and emergence of new viruses can go largely unnoticed. New tools are needed to increase the precision of arbovirus surveillance and control in preparation for climate change. Mosqlimate is a multi-disease tool with two main goals:
- estimate probabilities of change in pattern of disease transmission in response to climate and land use changes;
- identify circulating viruses during outbreaks when information is incomplete.
Mosqlimate will detect signs of expansion of arbovirus transmission areas, as well as signs of outbreaks potentially linked to new arboviruses. The tool will flexibly feed on climate and epidemiological data whenever available. OviCounter will fill in the mosquito data gap by providing digital technology to improve the use of eggtraps for mosquito surveillance at large scale. As output, Mosqlimate will deliver measures of risk to integrate into the Brazilian early warning system Infodengue and its mature community of practice. The ultimate goal of Mosqlimate is to improve the response to epidemiological challenges arising from climate change. Brazil is a continental country with a diversity of environmental and social conditions, all of them showing high vulnerability to the introduction of new viruses. But the frontier of expansion for these diseases do not respect country borders. Mosqlimate will seek to partner with similar initiatives in other countries, with particular emphasis on our South American neighbours.
Mosqlimate will feed on multiple data streams: Infodengue (incidence data), Climate forecasts and mosquito population density data (OviCounter) and run multi-arboviruses risk assessment models. Mosqlimate has two main endpoints: probability of regime shift, that is, change in pattern of disease transmission from sporadic to epidemic to endemic patterns in response to climate and land use changes; and an alarm model for arbovirus outbreaks by known or new viruses, that will detect signs of expansion of arbovirus transmission areas as well as signs of non-identified outbreaks potentially linked to new arboviruses.
