This is the first report of the ‘Observatório COVID191 - Grupo: Redes de Contágio – Laboratório de Estudos de Defesa’ for the South region of Brazil. We have combined data of confirmed cases of the new coronavirus (SARS-CoV-2) for the South available up to 17/04/2020, with structural analyses of road networks, from within and between states, to estimate the vulnerability and potential influence of the South micro-regions to propagate the disease.

Este é o primeiro relatório do Observatório COVID19 - Grupo: Redes de Contágio – Laboratório de Estudos de Defesa para a região Sul do Brasil. Combinamos dados de casos confirmados do novo coronavírus (SARS-CoV-2) para o Sul, disponíveis até o dia 17/04/2020, com análises estruturais da rede de rotas rodoviárias intra e interestaduais para estimarmos a vulnerabilidade e potencial influência das microrregiões sulinas na propagação da doença.

BACKGROUND Southeast Brazil has recently experienced a Yellow Fever virus (YFV) outbreak where the mosquito Haemagogus leucocelaenus was a primary vector. Climatic factors influence the abundance of mosquito vectors and arbovirus transmission. OBJECTIVES We aimed at describing the population dynamics of Hg. leucocelaenus in a county touched by the recent YFV outbreak. METHODS Fortnightly egg collections with ovitraps were performed from November 2012 to February 2017 in a forest in Nova Iguaçu, Rio de Janeiro, Brazil. The effects of mean temperature and rainfall on the Hg. leucocelaenus population dynamics were explored. FINDINGS Hg. leucocelaenus eggs were continuously collected throughout the study, with a peak in the warmer months (December-March). The climatic variables had a time-lagged effect and four weeks before sampling was the best predictor for the positivity of ovitraps and total number of eggs collected. The probability of finding > 50% positive ovitraps increased when the mean temperature was above 24ºC. The number of Hg. leucocelaenus eggs expressively increase when the mean temperature and accumulated precipitation surpassed 27ºC and 100 mm, respectively, although the effect of rainfall was less pronounced. MAIN CONCLUSIONS Monitoring population dynamics of Hg. leucocelaenus and climatic factors in YFV risk areas, especially mean temperature, may assist in developing climate-based surveillance procedures to timely strengthening prophylaxis and control.

The Pantanal is a South American biome characterized by extensive plains and stark environmental seasonality. Several habitats are subject to annual flooding, forcing small mammal species to aggregate in dry forest patches, which most likely influences their population dynamics and life history strategies. In order to investigate the seasonal influence on the life history traits of these small mammals, we conducted a 2-year mark-recapture study in the southeastern region of the Brazilian Pantanal (Nhecolândia) and analyzed the population dynamics of the most abundant small mammal species with the jackknife estimator. A trapping effort of 21,560 trap-nights resulted in 615 individuals in 1,171 captures (success = 5.43%). Three species of rodents - Oecomys mamorae (Thomas, 1906), Thrichomys pachyurus (Wagner, 1845), and Clyomys laticeps (Thomas, 1841) - and three species of marsupials - Gracilinanus agilis (Burmeister, 1854), Thylamys macrurus (Olfers, 1818), and Monodelphis domestica (Wagner, 1842) - were obtained. The most abundant species was O. mamorae, followed by G. agilis and T. pachyurus. Oecomys mamorae was more abundant in the wet season and presented an opportunistic reproductive strategy. Gracilianus agilis displayed increased population sizes in the dry season and synchronized, seasonal reproduction during the rainy season. Thrichomys pachyurus had a small population size, delayed response to variations in environmental conditions and higher reproductive rates in the dry season. All species revealed different life history strategies (seasonal, opportunistic or delayed response to environmental variations), coinciding with periods of higher resource availability in order to maximize survival.