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Nawa M, Mupeyo-Mudala C, Banda-Tembo S, Adetokunboh O. The effects of modern housing on malaria transmission in different endemic zones: a systematic review and meta-analysis. Malar J 2024; 23:235. [PMID: 39113048 PMCID: PMC11308589 DOI: 10.1186/s12936-024-05059-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 07/27/2024] [Indexed: 08/10/2024] Open
Abstract
BACKGROUND Modern housing has been shown to reduce the risk of malaria infections compared to traditional houses; however, it is unclear if the effects differ in different malaria transmission settings. This study evaluated the effects of modern housing on malaria among different endemic areas. METHODS Electronic databases, clinical trial registries and grey literature were searched for randomized controlled trials, cohort studies, case-control studies, and cross-sectional surveys on housing done between 1987 and 2022. Forest plots were done, and the quality of evidence was assessed using the Grading of Recommendations, Assessments, Development and Evaluation Framework. RESULTS Twenty-one studies were included; thirteen were cross-sectional, four were case-control and four were cohort studies. Cohort studies showed an adjusted risk ratio of 0.68 (95% CI 0.48-0.96), and cross-sectional studies indicated an adjusted odds ratio (aOR) of 0.79 (95%CI 0.75-0.83). By endemic transmission regions, the adjusted odds ratio in the high endemic settings was 0.80 (95%CI 0.76-085); in the moderate transmission regions, aOR = 0.76 (95%CI 0.67-0.85) and in the low transmission settings, aOR = 0.67 (95%CI 0.48-0.85). CONCLUSIONS The evidence from observational studies suggests that there are no differences in the protective effects of modern houses compared to traditional houses on malaria by endemicity level. This implies that good quality modern housing protects against malaria regardless of the malaria transmission settings.
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Affiliation(s)
- Mukumbuta Nawa
- Division of Epidemiology and Biostatistics, Stellenbosch University, Stellenbosch, Western Cape, South Africa.
- Department of Epidemiology and Biostatistics, Levy Mwanawasa Medical University, Lusaka, Zambia.
| | - Catherine Mupeyo-Mudala
- Department of Epidemiology and Biostatistics, Levy Mwanawasa Medical University, Lusaka, Zambia
| | - Sylvia Banda-Tembo
- Department of Epidemiology and Biostatistics, Levy Mwanawasa Medical University, Lusaka, Zambia
| | - Olatunji Adetokunboh
- Division of Epidemiology and Biostatistics, Stellenbosch University, Stellenbosch, Western Cape, South Africa
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, Western Cape, South Africa
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Carrasco-Escobar G, Qquellon J, Villa D, Cava R, Llanos-Cuentas A, Benmarhnia T. Time-Varying Effects of Meteorological Variables on Malaria Epidemiology in the Context of Interrupted Control Efforts in the Amazon Rainforest, 2000-2017. Front Med (Lausanne) 2021; 8:721515. [PMID: 34660633 PMCID: PMC8511324 DOI: 10.3389/fmed.2021.721515] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 08/27/2021] [Indexed: 11/25/2022] Open
Abstract
Successful malaria control interventions, mostly based on the training of health workers, distribution of insecticide-treated nets, and spraying, decrease malaria incidence; however, when these interventions are interrupted, a resurgence may occur. In the Peruvian Amazon, after discontinuing the control activities implemented by the PAMAFRO project (2006–2010)-a Global Fund-sponsored project for the strengthening of malaria control and surveillance in multiple countries in Latin America– malaria cases re-emerged dramatically. In parallel, meteorological factors determine the conditions suitable for the development, reproduction, and survival of mosquito vectors and parasites. This study hypothesized that interruption of malaria interventions may have modified the meteorological-malaria relationships over time (i.e., temporal changes in the dose-response between meteorological variables and malaria incidence). In this panel data analysis, we assessed the extent that relationships between meteorological variables and malaria changed temporally using data of monthly malaria incidence due to Plasmodium vivax or P. falciparum in Loreto, Peru (2000–2017). Generalized additive models were used to explore how the effects of meteorological variables changed in magnitude before, during, and after the PAMAFRO intervention. We found that once the PAMAFRO intervention had been interrupted, the estimated effects (dose-response) of meteorological variables on incidence rates decreased for both malaria parasite species. However, these fitted effect estimates did not reach their baseline levels (before the PAMAFRO period); variations of time-varying slopes between 0.45 and 2.07 times were observed after the PAMAFRO intervention. We also reported significant heterogeneity in the geographical distributions of malaria, parasite species, and meteorological variables. High malaria transmission occurred consistently in the northwestern provinces of Loreto Department. Since the end of the PAMAFRO period, a higher effect of precipitation and actual evapotranspiration was described on P. falciparum compared to P. vivax. The effect of temperature on malaria was greater over a shorter time (1-month lag or less), compared with precipitation and actual evapotranspiration (12-month lag). These findings demonstrate the importance of sustained malaria control efforts since interruption may enhance the links between meteorological factors and malaria. Our results also emphasize the importance of considering the time-varying effect of meteorological factors on malaria incidence to tailor control interventions, especially to better manage the current and future climate change crisis.
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Affiliation(s)
- Gabriel Carrasco-Escobar
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru.,Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, United States
| | - Jazmin Qquellon
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Diego Villa
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Renato Cava
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Alejandro Llanos-Cuentas
- Facultad de Salud Pública y Administración, Universidad Peruana Cayetano Heredia, Lima, Peru.,Instituto de Medicina Tropical "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Tarik Benmarhnia
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, United States.,Scripps Institution of Oceanography, University of California, San Diego, San Diego, CA, United States
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Forecasting Confirmed Malaria Cases in Northwestern Province of Zambia: A Time Series Analysis Using 2014–2020 Routine Data. ADVANCES IN PUBLIC HEALTH 2021. [DOI: 10.1155/2021/6522352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Background. Malaria remains a significant public health problem, especially in resource-poor settings. We aimed to forecast the year 2021 monthly confirmed malaria cases in the northwestern province of Zambia. Methods. The total number of confirmed monthly malaria cases recorded at health facilities over the past 7-years period (January 2014 to December 2020) was taken from the District Health Information System version 2 (DHIS.2) database. Box–Jenkins autoregressive integrated moving average (ARIMA) was used to forecast monthly confirmed malaria cases for 2021. STATA software version 16 was used for analyzing the time series data. Results. Between 2014 and 2020, there were 3,795,541 confirmed malaria cases in the northwestern province with a monthly mean of 45,185 cases. ARIMA (2, 1, 2) (0, 1, 1)12 was the best fit and the most parsimonious model. The forecasted mean monthly confirmed malaria cases were 60,284 (95%CI 30,969–121,944), and the total forecasted confirmed malaria cases were 723,413 (95%CI 371,626–1,463,322) for the year 2021. Conclusion. The forecasted confirmed malaria cases suggest that there will be an increase in the number of confirmed malaria cases for the year 2021 in the northwestern province. Therefore, there is a need for concerted efforts to prevent and eliminate the disease if the goal to eliminate malaria in Zambia by 2030 is to be realized.
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