| Autor: |
Klauss Kleydmann Sabino Garcia, Seyi Soremekun, Christian Bottomley, Amanda Amaral Abrahão, Cristiano Barreto de Miranda, Chris Drakeley, Walter Massa Ramalho, André M. Siqueira |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Malaria Journal, Vol 22, Iss 1, Pp 1-10 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1475-2875 |
| DOI: |
10.1186/s12936-023-04706-z |
| Popis: |
Abstract 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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