Relationship between the colours of the rivers in the Amazon and the incidence of malaria.

BACKGROUND: Malaria is transmitted by different Anopheles species. In Brazil, the disease is concentrated in the Amazon region. Rivers play an important role in the life cycle of malaria since the vector reproduces in aquatic environments. The waters of the rivers in the Amazon have distinct chemical characteristics, which affect the colour of the water and therefore, the study analysed whether the colour of the waters of the rivers have an on influence the distribution of malaria. The goal of the study was to correlate the different colourations of the water (black, white and mixed water) and the malaria incidence in 50 municipalities of the Amazonas state, Brazil, and then test hypotheses about the characteristics of the colour of the rivers and disease incidence. METHODS: This study was conducted for a period of seventeen years (2003-2019) in 50 municipalities in the state of Amazonas, Brazil. A conditionally Gaussian dynamic linear model was developed to analyse the association of malaria incidence and three types of river colour: white, black and mixed. RESULTS: The analyses indicate that the distribution of malaria is related to the colouration of the rivers. The results showed that places located near black-water rivers have a higher malaria incidence when compared to places on the banks of white-water rivers. CONCLUSIONS: Historically, the hydrological regime has played an important role in the dynamics of malaria in the Amazon, but little is known about the relationship between river colours and the incidence of the disease. This research was carried out in a region with hydrographic characteristics that were heterogeneous enough to allow an analysis that contrasted different colours of the rivers and covered almost the whole of the state of Amazonas. The results help to identify the places with the highest risk of malaria transmission and it is believed that they will be able to contribute to more precise planning of actions aimed at controlling the disease in the region.

An approximate likelihood estimator for the prevalence of infections in vectors using pools of varying sizes.

There are several arthropods that can transmit disease to humans. To make inferences about the rate of infection of these arthropods, it is common to collect a large sample of vectors, divide them into groups (called pools), and apply a test to detect infection. This paper presents an approximate likelihood point estimator to rate of infection for pools of different sizes, when the variability of these sizes is small and the infection rate is low. The performance of this estimator was evaluated in four simulated scenarios, created from real experiments selected in the literature. The new estimator performed well in three of these scenarios. As expected, the new estimator performed poorly in the scenario with great variability in the size of the pools for some values of the parameter space.