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In Brazil, 99% of malaria cases occur in the Amazon region, mainly caused by Plasmodium vivax (~83%) and Plasmodium falciparum (Pf) species. Aligned with the Sustainable Development Goals, Brazil aims to eliminate autochthonous malaria by 2035. This study aims to analyse epidemiological patterns of malaria in Brazil to discuss if Brazil is on track to meet malaria control targets. A time-series study was conducted analysing autochthonous malaria new infections notifications in the Brazilian Amazon region from 2011 until June 2023. Descriptive analyses were conducted, along with joinpoint regression and forecast models to verify trend and future behaviour. A total of 2,067,030 malaria cases were reported in the period. Trend analysis indicated a decreasing trend in all malaria infections since late 2017 (monthly reduction = 0.81%, p-value <0.05), while Pf infections have increased progressively since 2015 (monthly increase = 0.46%, p-value <0.05). Forecast models predict over 124,000 malaria cases in 2023 and over 96,000 cases in 2024. Predictions for Pf infections are around 23,900 cases in 2023 and 22,300 in 2024. Cases in indigenous population villages are predicted to reach 48,000 cases in 2023 and over 51,000 in 2024. In gold mining areas it is expected over 21,000 cases in 2023 and over 20.000 in 2024. Malaria elimination in Brazil has advanced over the last decade, but its speed has slowed. The country exhibits noteworthy advancements in the reduction of overall malaria cases. It is imperative, however, to proactively target specific issues such as the incidence raise among indigenous populations and in gold mining areas. Pf infections remain a persistent challenge to control in the country and may require novel measures for containment. Current government supporting actions towards combating illegal goldmining activities and protecting indigenous populations may help malaria control indicators for the following years.
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OBJECTIVE: The objective is to describe the results and the methodological processes of record linkage for matching deaths and malaria cases. METHODS: A descriptive cross-sectional study was conducted with probabilistic record linkage of death and malaria cases data in Brazil from 2011 to 2020 using death records from the Mortality Information System (SIM) and epidemiological data from the Notifiable Diseases Information System (Sinan) and Epidemiological Surveillance Information Systems for malaria (Sivep-Malaria). Three matching keys were used: patient's name, date of birth, and mother's name, with an analysis of cosine and Levenshtein dissimilarity measures. RESULTS: A total of 490 malaria deaths were recorded in Brazil between 2011 and 2020. The record linkage resulted in the pairing of 216 deaths (44.0%). Pairings where all three matching keys were identical accounted for 30.1% of the total matched deaths, 39.4% of the matched deaths had two identical variables, and 30.5% had only one of the three key variables identical. The distribution of the variables of the matched deaths (216) was similar to the distribution of all recorded deaths (490). Out of the 216 matched deaths, 80 (37.0%) had poorly specified causes of death in the SIM. CONCLUSIONS: The record linkage allowed for the detailing of the data with additional information from other epidemiological systems. Record linkage enables data linkage between information systems that lack interoperability and is an extremely useful tool for refining health situation analyses and improving malaria death surveillance in Brazil.
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BACKGROUND: In 2021, Brazil was responsible for more than 25% of malaria cases in the Americas. Although the country has shown a reduction of cases in the last decades, in 2021 it reported over 139,000 malaria cases. One major malaria control strategy implemented in Brazil is the "Malaria Supporters Project", which has been active since 2012 and is directed to municipalities responsible for most Brazil's cases. The objective of this study is to analyse the intervention effect on the selected municipalities. METHODS: An ecological time-series analysis was conducted to assess the "Malaria Supporters Project" effect. The study used data on Annual Parasitic Incidence (API) spanning the period from 2003 to 2020 across 48 intervention municipalities and 88 control municipalities. To evaluate the intervention effect a Prais-Winsten segmented regression model was fitted to the difference in malaria Annual Parasitic Incidence (API) between control and intervention areas. RESULTS: The intervention group registered 1,104,430 cases between 2012 and 2020, a 50.6% reduction compared to total cases between 2003 and 2011. In 2020 there were 95,621 cases, 50.4% fewer than in 2011. The number of high-risk municipalities (API > 50 cases/1000) reduced from 31 to 2011 to 17 in 2020. The segmented regression showed a significant 42.0 cases/1000 residents annual decrease in API compared to control group. CONCLUSIONS: The intervention is not a silver bullet to control malaria, but it has reduced API in locations with high malaria endemicity. Furthermore, the model has the potential to be replicated in other countries with similar epidemiological scenarios.
Assuntos
Malária , Humanos , Brasil/epidemiologia , Análise de Séries Temporais Interrompida , Malária/epidemiologia , Malária/prevenção & controle , Projetos de Pesquisa , ConvulsõesRESUMO
BACKGROUND: Antibody responses to sand fly saliva have been suggested to be a useful marker of exposure to sand fly bites and Leishmania infection and a potential tool to monitor the effectiveness of entomological interventions. Exposure to sand fly bites before infection has also been suggested to modulate the severity of the infection. Here, we test these hypotheses by quantifying the anti-saliva IgG response in a cohort study of dogs exposed to natural infection with Leishmania infantum in Brazil. METHODS: IgG responses to crude salivary antigens of the sand fly Lutzomyia longipalpis were measured by ELISA in longitudinal serum samples from 47 previously unexposed sentinel dogs and 11 initially uninfected resident dogs for up to 2 years. Antibody responses were compared to the intensity of transmission, assessed by variation in the incidence of infection between seasons and between dogs. Antibody responses before patent infection were then compared with the severity of infection, assessed using tissue parasite loads and clinical symptoms. RESULTS: Previously unexposed dogs acquired anti-saliva antibody responses within 2 months, and the rate of acquisition increased with the intensity of seasonal transmission. Over the following 2 years, antibody responses varied with seasonal transmission and sand fly numbers, declining rapidly in periods of low transmission. Antibody responses varied greatly between dogs and correlated with the intensity of transmission experienced by individual dogs, measured by the number of days in the field before patent infection. After infection, anti-saliva antibody responses were positively correlated with anti-parasite antibody responses. However, there was no evidence that the degree of exposure to sand fly bites before infection affected the severity of the infection. CONCLUSIONS: Anti-saliva antibody responses are a marker of current transmission intensity in dogs exposed to natural infection with Leishmania infantum, but are not associated with the outcome of infection.