Vector competence, vectorial capacity of Nyssorhynchus darlingi and the basic reproduction number of Plasmodium vivax in agricultural settlements in the Amazonian Region of Brazil.

BACKGROUND: Brazilian malaria control programmes successfully reduced the incidence and mortality rates from 2005 to 2016. Since 2017, increased malaria has been reported across the Amazon. Few field studies focus on the primary malaria vector in high to moderate endemic areas, Nyssorhynchus darlingi, as the key entomological component of malaria risk, and on the metrics of Plasmodium vivax propagation in Amazonian rural communities. METHODS: Human landing catch collections were carried out in 36 houses of 26 communities in five municipalities in the Brazilian states of Acre, Amazonas and Rondônia states, with API (> 30). In addition, data on the number of locally acquired symptomatic infections were employed in mathematical modelling analyses carried out to determine Ny. darlingi vector competence and vectorial capacity to P. vivax; and to calculate the basic reproduction number for P. vivax. RESULTS: Entomological indices and malaria metrics ranged among localities: prevalence of P. vivax infection in Ny. darlingi, from 0.243% in Mâncio Lima, Acre to 3.96% in Machadinho D'Oeste, Rondônia; daily human-biting rate per person from 23 ± 1.18 in Cruzeiro do Sul, Acre, to 66 ± 2.41 in Lábrea, Amazonas; vector competence from 0.00456 in São Gabriel da Cachoeira, Amazonas to 0.04764 in Mâncio Lima, Acre; vectorial capacity from 0.0836 in Mâncio Lima, to 1.5 in Machadinho D'Oeste. The estimated R0 for P. vivax (PvR0) was 3.3 in Mâncio Lima, 7.0 in Lábrea, 16.8 in Cruzeiro do Sul, 55.5 in São Gabriel da Cachoeira, and 58.7 in Machadinho D'Oeste. Correlation between P. vivax prevalence in Ny. darlingi and vector competence was non-linear whereas association between prevalence of P. vivax in mosquitoes, vectorial capacity and R0 was linear and positive. CONCLUSIONS: In spite of low vector competence of Ny. darlingi to P. vivax, parasite propagation in the human population is enhanced by the high human-biting rate, and relatively high vectorial capacity. The high PvR0 values suggest hyperendemicity in Machadinho D'Oeste and São Gabriel da Cachoeira at levels similar to those found for P. falciparum in sub-Saharan Africa regions. Mass screening for parasite reservoirs, effective anti-malarial drugs and vector control interventions will be necessary to shrinking transmission in Amazonian rural communities, Brazil.

The influence of climate variables on dengue in Singapore.

In this work we correlated dengue cases with climatic variables for the city of Singapore. This was done through a Poisson Regression Model (PRM) that considers dengue cases as the dependent variable and the climatic variables (rainfall, maximum and minimum temperature and relative humidity) as independent variables. We also used Principal Components Analysis (PCA) to choose the variables that influence in the increase of the number of dengue cases in Singapore, where PC1 (Principal component 1) is represented by temperature and rainfall and PC2 (Principal component 2) is represented by relative humidity. We calculated the probability of occurrence of new cases of dengue and the relative risk of occurrence of dengue cases influenced by climatic variable. The months from July to September showed the highest probabilities of the occurrence of new cases of the disease throughout the year. This was based on an analysis of time series of maximum and minimum temperature. An interesting result was that for every 2-10°C of variation of the maximum temperature, there was an average increase of 22.2-184.6% in the number of dengue cases. For the minimum temperature, we observed that for the same variation, there was an average increase of 26.1-230.3% in the number of the dengue cases from April to August. The precipitation and the relative humidity, after analysis of correlation, were discarded in the use of Poisson Regression Model because they did not present good correlation with the dengue cases. Additionally, the relative risk of the occurrence of the cases of the disease under the influence of the variation of temperature was from 1.2-2.8 for maximum temperature and increased from 1.3-3.3 for minimum temperature. Therefore, the variable temperature (maximum and minimum) was the best predictor for the increased number of dengue cases in Singapore.