Is Brazil reaching malaria elimination? A time series analysis of malaria cases from 2011 to 2023.

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.

Record Linkage for Malaria Deaths Data Recovery and Surveillance in Brazil.

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.

Assessing the impact of the "malaria supporters project" intervention to malaria control in the Brazilian Amazon: an interrupted time-series analysis.

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.

Malaria time series in the extra-Amazon region of Brazil: epidemiological scenario and a two-year prediction model.

BACKGROUND: In Brazil, malaria is caused mainly by the Plasmodium vivax and Plasmodium falciparum species. Its transmission occurs in endemic and non-endemic areas. Malaria geography in Brazil has retracted and is now concentrated in the North region. The Brazilian Amazon region accounts for 99% of Brazil's cases. Brazil's extra-Amazon region has a high frequency of imported cases and in 2019 presented a mortality rate 123 times higher than the Amazon region. Extra-Amazon cases present risks of reintroduction. This study aims to characterize the epidemiological scenario for malaria in the extra-Amazon region of Brazil from 2011 to 2020 with a two-year forecast. METHODS: Time-series study with description of malaria cases and deaths registered in Brazilian extra-Amazon region from 2011 to 2020. Public data from the Notifiable Diseases Information System (Sinan) and the Mortality Information System (SIM) were used. Descriptive analysis, incidence, and notification rates were calculated. Flow charts analysed the flux between Places of Probable Infection (PI) and places of notification. The prediction model utilized a multiplicative Holt-winters model for trend and seasonality components. RESULTS: A total of 6849 cases were registered. Cases were predominantly white males with 9 to 11 years of education, mostly between 30 and 39 years old. Imported cases accounted for 78.9% of cases. Most frequent occupations for imported cases are related to travelling and tourism activities. Among autochthonous cases, there is a higher frequency of agriculture and domestic economic activities. In the period there were 118 deaths due to malaria, of which 34.7% were caused by P. falciparum infections and 48.3% were not specified. The most intense flows of imported cases are from Amazonas and Rondônia to São Paulo, Rio de Janeiro, and Paraná. The prediction estimates around 611 cases for each of the following two years. CONCLUSION: The time series allows a vast epidemiological visualization with a short-term prediction analysis that supports public health planning. Government actions need to be better directed in the extra-Amazon region so the objective of eliminating malaria in Brazil is achieved. Carrying out quality assessments for information systems and qualifying personnel is advisable. Malaria outside the Amazon region is mainly due to imported cases and delay in diagnosis is associated with a higher fatality rate. Better strategies to diagnose and treat suspected cases can lead to lower risk of deaths and local outbreaks that will be important for achieving malaria elimination in Brazil.

Costs of Guillain-Barré Syndrome in the Brazilian Federal District: the patients' perspective.

BACKGROUND: Although rare, Guillain-Barré Syndrome (GBS) has a high economic burden, with consequences for families and society. This study aimed to estimate the total cost of GBS, per individual and per variant of the disease, as well as its effect on household income, from the perspective of patients. METHODS: This was a cost-of-illness study from the perspective of patients and their families, with a time horizon from disease onset to 6 mo after discharge. The total cost of GBS was estimated by bottom-up microcosting, considering direct and indirect costs. RESULTS: The median cost of GBS per individual was US$1635.5, with direct costs accounting for 64.3% of this amount. Among the variants analyzed, acute motor sensory axonal neuropathy (US$4660.1) and acute inflammatory demyelinating polyneuropathy (US$2017.0) exhibited the highest costs compared with acute motor axonal neuropathy (US$1635.5) and Miller Fisher Syndrome (US$1464.8). The costs involved compromise more than 20% of the household income of 22 (47.8%) patients. CONCLUSIONS: This study demonstrated how costly GBS can be. It is hoped that decision-makers will analyze these results with a view to improving the structure of healthcare services.

Research Development Using REDCap Software.

OBJECTIVES: High-quality clinical research is dependent on adequate design, methodology, and data collection. The utilization of electronic data capture (EDC) systems is recommended to optimize research data through proper management. This paper's objective is to present the procedures of REDCap (Research Electronic Data Capture), which supports research development, and to promote the utilization of this software among the scientific community. METHODS: REDCap's web application version 10.4.1 released on 2021 (Vanderbilt University) is an EDC system suitable for clinical research development. This paper describes how to join the REDCap consortium and presents how to develop survey instruments and use them to collect and analyze data. RESULTS: Since REDCap is a web application that stimulates knowledge-sharing among the scientific community, its development is not finished and it is constantly receiving updates to improve the system. REDCap's tools provide access control, audit trails, and data security to the research team. CONCLUSIONS: REDCap is a web application that can facilitate clinical research development, mainly in health fields, and reduce the costs of conducting research. Its tools allow researchers to make the best use of EDC components, such as data storage.

Sensitivity of Guillain-Barre Syndrome Surveillance in the Brazilian Federal District, using the Capture-Recapture Method.

INTRODUCTION: Guillain-Barre Syndrome (GBS) is an acute immune-mediated polyneuropathy that compromises the peripheral and cranial nerves. It is characterized by rapid-onset paresthesia accompanied by progressive weakness in the lower extremities followed by symmetric ascending paralysis. METHODOLOGY: assessment of sensitivity to detect GBS between March 2017 and May 2019 in a public referral hospital, using the capture-recapture method based on the Chapman estimator and comparing three GBS data sources: the hospital-based sentinel surveillance system (VSBH), Human Immunoglobulin Dispensing Records System (RDIH), and Hospital Information System (SIH). RESULTS: A total of 259 possible cases were identified (captured). Of these, 58 were confirmed and most resided in the Federal District. The VSBH showed the greatest sensitivity in case identification. The temporal distribution of cases showed periods with no cases identified, and more were registered during the rainy season from October to May, when high temperatures also occur. CONCLUSIONS: Increased circulation of arboviruses and gastrointestinal infections during the rainy season may explain the greater concentration of GBS cases. It is important to note that one-third of the cases identified in the different data sources do not converge, demonstrating that no single surveillance system is 100% effective. The severity and possible increase in cases related to GBS demonstrates the need for an improved surveillance system capable of monitoring and following-up cases involving neurological syndromes, regardless of the event preceding infection.

Ten Epidemiological Parameters of COVID-19: Use of Rapid Literature Review to Inform Predictive Models During the Pandemic.

Objective: To describe the methods used in a rapid review of the literature and to present the main epidemiological parameters that describe the transmission of SARS-Cov-2 and the illness caused by this virus, coronavirus disease 2019 (COVID-19). Methods: This is a methodological protocol that enabled a rapid review of COVID-19 epidemiological parameters. Findings: The protocol consisted of the following steps: definition of scope; eligibility criteria; information sources; search strategies; selection of studies; and data extraction. Four reviewers and three supervisors conducted this review in 40 days. Of the 1,266 studies found, 65 were included, mostly observational and descriptive in content, indicating relative homogeneity as to the quality of the evidence. The variation in the basic reproduction number, between 0.48 and 14.8; and the median of the hospitalization period, between 7.5 and 20.5 days stand out as key findings. Conclusion: We identified and synthesized 10 epidemiological parameters that may support predictive models and other rapid reviews to inform modeling of this and other future public health emergencies.