Exploring the influence of deforestation on dengue fever incidence in the Brazilian Amazonas state.

INTRODUCTION: Dengue fever is the most prevalent arboviral disease in the Brazilian Amazon and places a major health, social and economic burden on the region. Its association with deforestation is largely unknown, yet the clearing of tropical rainforests has been linked to the emergence of several infectious diseases, including yellow fever and malaria. This study aimed to explore potential drivers of dengue emergence in the Brazilian Amazon with a focus on deforestation. METHODS: An ecological study design using municipality-level secondary data from the Amazonas state between 2007 and 2017 (reported rural dengue cases, incremental deforestation, socioeconomic characteristics, healthcare and climate factors) was employed. Data were transformed according to the year with the most considerable deforestation. Associations were explored using bivariate analysis and a multivariate generalised linear model. RESULTS: During the study period 2007-2017, both dengue incidence and deforestation increased. Bivariate analysis revealed increased incidences for some years after deforestation (e.g. mean difference between dengue incidence before and three years after deforestation was 55.47 cases per 100,000, p = 0.002), however, there was no association between the extent of deforestation and dengue incidence. Using a negative binomial regression model adjusted for socioeconomic, climate and healthcare factors, deforestation was not found to be related to dengue incidence. Access to healthcare was found to be the only significant predictor of dengue incidence. DISCUSSION: Previous research has shown that deforestation facilitates the emergence of vector-borne diseases. However, no significant dose-response relationships between dengue incidence and deforestation in the Brazilian Amazonas state were found in this study. The finding that access to healthcare was the only significant predictor of dengue incidence suggests that incidence may be more dependent on surveillance than transmission. Further research and public attention are needed to better understand environmental effects on human health and to preserve the world's largest rainforest

Linking surveillance and climate data to combat malaria

Introduction Malaria is an infectious disease that affected nearly 215 million individuals in 2015. In Brazil, there are various information systems targeted to store data from disease notification, including malaria surveillance. However, these databases are identified and difficult to be accessed by researchers due to privacy restrictions. Objectives and Approach Our goal is to integrate data from two different malaria surveillance systems, as well climate, hydrographics and socioeconomic data, to support ecological and cohort-based analyzes on malaria recurrence, parasitic classification assisted by machine learning methods and epidemics forecasting. Our approach so far was to generate data sets organized by municipality of residence and by municipality of infection and the disposal of these data sets with information aggregated on monthly and annual basis. We expect these databases can be freely used by any researcher intending to conduct studies on malaria using governmental data. Results Our current results comprise data sets with information aggregated by municipality of residence, for all municipalities within the Amazonian region (n=772), and by municipalities of infection with active transmission (n=613). For both case, we added variables referring to demographic, socioeconomic, climatological and hydrological data for the period 2010 to 2015 in an annual and monthly form. We also performed a machine learning-based classification to group notifications according to the type of parasite into P. vivax, P. falciparum and mixed cases. Our goal is to identify similar and different characteristics among such groups that can be used to correctly assess recurrence, as well support epidemic forecasting. Conclusion/Implications From the databases we created, it will be possible to implement an indexing structure with related metadata, as well publicize these databases to allow for free access by researchers. Currently, we are also running different predictive analytics methods (including visualisation) targeted to generate a forecast model for malaria epidemics

Binary Models for Arboviruses Classification Using Machine Learning: A Benchmarking Evaluation

Arboviral diseases are common worldwide. Infection with arboviruses can lead to serious health problems, even death in severe cases. Such health problems can be prevented by the early and correct detection of these arboviruses, but this is challenging due to the overlap of their symptoms. In this work, we benchmark different Machine Learning (ML) models to classify two types of arboviruses. We propose two distinct binary models: (i) a model to classify if the patient has arbovirus or another disease; and (ii) a model to classify if the patient has Dengue or Chikungunya. We configure and evaluate several ML models using hyperparameter optimization and feature selection techniques. The Random Forest and XGboost tree-based models present the best results with over 80% recall in the Chikungunya and Inconclusive classes

Declining malaria transmission in rural Amazon: changing epidemiology and challenges to achieve elimination

BACKGROUND: In recent years, considerable success in reducing its incidence has been achieved in Brazil, leading to a relative increase in the proportion of cases caused by Plasmodium vivax, considered a harder-to-eliminate parasite. This study aim is to describe the transmission dynamics and associated risk factors in a rural settlement area in the Western Brazilian Amazon. METHODS: A prospective cohort was established in a rural settlement area for 3 years. Follow-up included continuous passive case detection and monthly active case detection for a period of 6 months. Demographic, clinical and transmission control practices data were collected. Malaria diagnosis was performed through thick blood smear. Univariable and multivariable analyses of factors associated with malaria incidence were performed using negative binomial regression models. Factors associated with recurrence of P. vivax and Plasmodium falciparum malaria within 90 days of a previous episode were analysed using univariable and multivariable Cox-Proportional Hazard models. RESULTS: Malaria prevalence decreased from 7 % at the study beginning to 0.6 % at month 24, with P. vivax predominating and P. falciparum disappearing after 1 year of follow-up. Malaria incidence was significantly higher in the dry season [IRR (95 % CI) 1.4 (1.1-1.6); p < 0.001)]. Use of ITN was associated to malaria protection in the localities [IRR (95 % CI) 0.7 (0.6-0.8); p = 0.001)]. A recurrent P. vivax episode within 90 days was observed in 29.4 % of individuals after an initial diagnosis. A previous P. vivax [IRR (95 % CI) 2.3 (1.3-4.0); p = 0.006)] or mixed P. vivax + P. falciparum [IRR (95 % CI) 2.9 (1.5-5.7); p = 0.002)] infections were significantly associated to a vivax malaria episode within 90 days of follow-up. CONCLUSIONS: In an area of P. falciparum and P. vivax co-endemicity, a virtual disappearance of P. falciparum was observed with P. vivax increasing its relative contribution, with a large proportion of recurring episodes. This finding reinforces the perception of P. falciparum being more responsive to early diagnosis and treatment and ITN use and the contribution of relapsing P. vivax to maintain this species' transmission. In areas of P. vivax endemicity, antihypnozoite treatment effectiveness assessment in different transmission intensity may be a fundamental activity for malaria control and elimination

A Brazilian classified data set for prognosis of tuberculosis, between January 2001 and April 2020

After COVID-19, tuberculosis (TB) is the leading cause of death by an infectious disease in the world. This work presents a data set based on data collected from the Brazilian Information System for Notifiable Diseases (SINAN) for the period from January 2001 to April 2020 relating to patients diagnosed with tuberculosis in Brazil. The data from SINAN was pre-processed to generate a new data set with two distinct treatment outcome classes: CURED and DIED. The data set comprises 37 categorical attributes (including socio-demographic, clinical, and laboratory data) as well as the target class. There are 927,909 records of patients classified as CURED and 36,190 classified as DIED, totaling 964,099 records

Prevalence and force of Plasmodium vivax blood-stage infection and associated clinical malaria burden in the Brazilian Amazon

BACKGROUND: Understanding the epidemiology of malaria through the molecular force of the blood-stage infection of Plasmodium vivax (molFOB) may provide a detailed assessment of malaria transmission. OBJECTIVES: In this study, we investigated risk factors and spatial-temporal patterns of incidence of Plasmodium infection and clinical malaria episodes in three peri-urban communities of Manaus, Western Brazilian Amazon. METHODS: Monthly samples were collected in a cohort of 1,274 individuals between April 2013 and March 2014. DNA samples were subject to Plasmodium species. molFOB was calculated by counting the number of genotypes observed on each visit, which had not been present in the preceding two visits and adjusting these counts by the respective times-at-risk. FINDINGS: Respectively, 77.8% and 97.2% of the population remained free of P. vivax and P. falciparum infection. Expected heterozygosity for P. vivax was 0.69 for MSP1_F3 and 0.86 for MS2. Multiplicity of infection in P. vivax was close to the value of 1. The season was associated with P. vivax positivity [adjusted hazard ratio (aHR) 2.6 (1.9-5.7)] and clinical disease [aHR 10.6 (2.4-47.2)]. P. falciparum infection was associated with previous malarial episodes [HR 9.7 (4.5-20.9)]. Subjects who reported possession of a bed net [incidence rate ratio (IRR) 1.6 (1.2-2.2)] or previous malaria episodes [IRR 3.0 (2.0-4.5)] were found to have significantly higher P. vivax molFOB. MAIN CONCLUSIONS: Overall, P. vivax infection prevailed in the area and infections were mostly observed as monoclonal. Previous malaria episodes were associated with significantly higher P. vivax molFOB

Association of TLR variants with susceptibility to Plasmodium vivax malaria and parasitemia in the Amazon region of Brazil

BACKGROUND: Plasmodium vivax malaria (Pv-malaria) is still considered a neglected disease despite an alarming number of individuals being infected annually. Malaria pathogenesis occurs with the onset of the vector-parasite-host interaction through the binding of pathogen-associated molecular patterns (PAMPs) and receptors of innate immunity, such as toll-like receptors (TLRs). The triggering of the signaling cascade produces an elevated inflammatory response. Genetic polymorphisms in TLRs are involved in susceptibility or resistance to infection, and the identification of genes involved with Pv-malaria response is important to elucidate the pathogenesis of the disease and may contribute to the formulation of control and elimination tools. METHODOLOGY/PRINCIPAL FINDINGS: A retrospective case-control study was conducted in an intense transmission area of Pv-malaria in the state of Amazonas, Brazil. Genetic polymorphisms (SNPs) in different TLRs, TIRAP, and CD14 were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis in 325 patients infected with P. vivax and 274 healthy individuals without malaria history in the prior 12 months from the same endemic area. Parasite load was determined by qPCR. Simple and multiple logistic/linear regressions were performed to investigate association between the polymorphisms and the occurrence of Pv-malaria and parasitemia. The C/T (TLR5 R392StopCodon) and T/T (TLR9 -1486C/T) genotypes appear to be risk factors for infection by P. vivax (TLR5: C/C vs. C/T [OR: 2.116, 95% CI: 1.054-4.452, p = 0.031]; TLR9: C/C vs. T/T [OR: 1.919, 95% CI: 1.159-3.177, p = 0.010]; respectively). Fever (COEF = 7599.46, 95% CI = 3063.80-12135.12, p = 0.001) and the C/C genotype of TLR9 -1237C/T (COEF = 17006.63, 95% CI = 3472.83-30540.44, p = 0.014) were independently associated with increased parasitemia in patients with Pv-malaria. CONCLUSIONS: Variants of TLRs may predispose individuals to infection by P. vivax. The TLR5 R392StopCodon and TLR9 -1486C/T variants are associated with susceptibility to Pv-malaria. Furthermore, the TLR9 variant -1237C/C correlates with high parasitemia

Acceptability of short message service (SMS) as a tool for malaria treatment adherence in the Brazilian Amazon: a qualitative study

Background: Malaria is one of the leading causes of morbidity worldwide, and patient adherence to prescribed antimalarials is essential for effective treatment. Methods: This cross-sectional study, with in-depth telephone interviews, analyzed participants’ perceptions of short message service (SMS) in adherence to treatment. Results: Five thematic categories emerged: decreased forgetfulness, the novelty of the tool, easy-to-understand language, the impact of SMS messages during treatment, and suggestions for improvement and complaints. Conclusions: SMS could assist patients in adhering to prescribed antimalarials.Fil: Rodovalho, Sheila. Universidade do Estado do Amazonas; BrasilFil: Dias, Ádila Liliane Barros. Universidade do Estado do Amazonas; BrasilFil: Paz Ade, Maria. Pan American Health Organization; ArgentinaFil: Saint Gerons, Diego Macias. Pan American Health Organization; ArgentinaFil: Castro, Jose Luis. Pan American Health Organization; ArgentinaFil: Beratarrechea, Andrea Gabriela. Instituto de Efectividad Clínica y Sanitaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Murta, Felipe Leão Gomes. Universidade do Estado do Amazonas; BrasilFil: dos Santos, Alicia Cacau Patrine. Universidade do Estado do Amazonas; BrasilFil: Marques, Leonardo Lincoln Gomes. Universidade do Estado do Amazonas; BrasilFil: Sampaio, Vanderson Souza. Universidade do Estado do Amazonas; BrasilFil: Baia da Silva, Djane Clarys. Fundación Oswaldo Cruz; Brasil. Universidade do Estado do Amazonas; BrasilFil: Monteiro, Wuelton Marcelo. Universidade do Estado do Amazonas; Brasi

Plasmodium vivax malaria elimination : should innovative ideas from the past be revisited?

In the 1950s, the strategy of adding chloroquine to food salt as a prophylaxis against malaria was considered to be a successful tool. However, with the development of Plasmodium resistance in the Brazilian Amazon, this control strategy was abandoned. More than 50 years later, asexual stage resistance can be avoided by screening for antimalarial drugs that have a selective action against gametocytes, thus old prophylactic measures can be revisited. The efficacy of the old methods should be tested as complementary tools for the elimination of malaria