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Pons-Duran C, Mombo-Ngoma G, Macete E, Desai M, Kakolwa MA, Zoleko-Manego R, Ouédragou S, Briand V, Valá A, Kabanywanyi AM, Ouma P, Massougbodji A, Sevene E, Cot M, Aponte JJ, Mayor A, Slutsker L, Ramharter M, Menéndez C, González R. Burden of malaria in pregnancy among adolescent girls compared to adult women in 5 sub-Saharan African countries: A secondary individual participant data meta-analysis of 2 clinical trials. PLoS Med 2022; 19:e1004084. [PMID: 36054101 PMCID: PMC9439219 DOI: 10.1371/journal.pmed.1004084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 08/03/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Malaria is among the top causes of death in adolescent girls (10 to 19 years) globally. Adolescent motherhood is associated with increased risk of adverse maternal and neonatal outcomes. The interaction of malaria, adolescence, and pregnancy is especially relevant in malaria endemic areas, where rates of adolescent pregnancy are high. However, data on burden of malaria among adolescent girls are limited. This study aimed at investigating whether adolescent girls were at a greater risk of experiencing malaria-related outcomes in pregnancy-parasitaemia and clinical disease-than adult women. METHODS AND FINDINGS An individual secondary participant-level meta-analysis was conducted using data from 5,804 pregnant women participating in 2 malaria prevention clinical trials in Benin, Gabon, Kenya, Mozambique, and Tanzania between 2009 and 2014. Of the sample, 1,201 participants were adolescent girls with a mean age of 17.5 years (standard deviation (SD) 1.3) and 886 (73.8%) of them primigravidae. Among the 4,603 adult women with mean age of 27.0 years (SD 5.4), 595 (12.9%) were primigravidae. Mean gestational age at enrolment was 20.2 weeks (SD 5.2) and 1,069 (18.4%) participants were HIV-infected. Women were followed monthly until the postpartum visit (1 month to 6 weeks after delivery). This study considered outcomes including clinical episodes during pregnancy, peripheral parasitaemia at delivery, and placental malaria. A 2-stage meta-analysis approach was followed by pooling single multivariable regression results into standard DerSimonian-Laird random-effects models. Adolescent girls were more likely than adult women to present with clinical malaria during pregnancy (incidence risk ratio (IRR) 1.70, 95% confidence interval (CI) 1.20; 2.39, p-value = 0.003, I2 = 0.0%, N = 4,092), peripheral parasitaemia at delivery (odds ratio (OR) 2.28, 95% CI 1.46; 3.55, p-value < 0.001, I2 = 0.0%, N = 3,977), and placental infection (OR 1.97, 95% CI 1.31; 2.98, p-value = 0.001, I2 = 1.4%, N = 4,797). Similar associations were observed among the subgroup of HIV-uninfected participants: IRR 1.72 (95% CI 1.22; 2.45, p-value = 0.002, I2 = 0.0%, N = 3,531) for clinical malaria episodes, OR 2.39 (95% CI 1.49; 3.86, p-value < 0.001, I2 = 0.0%, N = 3,053) for peripheral parasitaemia, and OR 1.88 (95% CI 1.06 to 3.33, p-value = 0.03, I2 = 34.9%, N = 3,847) for placental malaria. Among HIV-infected subgroups statistically significant associations were not observed. Similar associations were found in the subgroup analysis by gravidity. The small sample size and outcome prevalence in specific countries limited the inclusion of some countries in the meta-analysis. Furthermore, peripheral parasitaemia and placental malaria presented a considerable level of missing data-12.6% and 18.2% of participants had missing data on those outcomes, respectively. Given the original scope of the clinical trials, asymptomatic malaria infection was only assessed at the end of pregnancy through peripheral and placental parasitaemia. CONCLUSIONS In this study, we observed that adolescent girls in sub-Saharan Africa (SSA) are more prone to experience clinical malaria episodes during pregnancy and have peripheral malaria and placental infection at delivery than adult women. Moreover, to the best of our knowledge, for the first time this study disaggregates figures and stratifies analyses by HIV infection. Similar associations were found for both HIV-infected and uninfected women, although those for HIV-infected participants were not statistically significant. Our finding suggests that adolescent girls may benefit from targeted malaria prevention strategies even before they become pregnant.
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Affiliation(s)
- Clara Pons-Duran
- ISGlobal, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain.,Consorcio de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Ghyslain Mombo-Ngoma
- Centre de Recherches Médicales de Lambaréné (CERMEL), Lambaréné, Gabon.,Institute of Tropical Medicine, Travel Medicine and Human Parasitology, University Clinics, Eberhard Karls University Tübingen, Tübingen, Germany.,Department of Tropical Medicine, Bernhard Nocht Institute for Tropical Medicine & Dept. of Medicine University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Eusebio Macete
- Manhiça Health Research Center (CISM), Manhiça, Mozambique
| | - Meghna Desai
- Malaria Branch, Division of Parasitic Diseases and Malaria, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | | | - Rella Zoleko-Manego
- Centre de Recherches Médicales de Lambaréné (CERMEL), Lambaréné, Gabon.,Institute of Tropical Medicine, Travel Medicine and Human Parasitology, University Clinics, Eberhard Karls University Tübingen, Tübingen, Germany.,Department of Tropical Medicine, Bernhard Nocht Institute for Tropical Medicine & Dept. of Medicine University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Smaïla Ouédragou
- Département de santé publique, Unité de formation en sciences de la santé, Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso.,Faculté de Sciences de la Santé, Université d'Abomey-Calavi, Cotonou, Bénin
| | - Valérie Briand
- Université de Paris, MERIT, IRD, Paris, France.,IRD, Inserm, Université de Bordeaux, IDLIC team, UMR 1219, Bordeaux, France
| | - Anifa Valá
- Manhiça Health Research Center (CISM), Manhiça, Mozambique
| | | | - Peter Ouma
- Malaria Branch, Division of Parasitic Diseases and Malaria, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.,Department of Medical Laboratory Sciences, Maseno University School of Medicine, Kenya
| | | | - Esperança Sevene
- Manhiça Health Research Center (CISM), Manhiça, Mozambique.,Department of Physiological Science, Clinical Pharmacology, Faculty of Medicine, Eduardo Mondlane University, Maputo, Mozambique
| | - Michel Cot
- Université de Paris, MERIT, IRD, Paris, France
| | - John J Aponte
- ISGlobal, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain.,Manhiça Health Research Center (CISM), Manhiça, Mozambique
| | - Alfredo Mayor
- ISGlobal, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain.,Consorcio de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,Manhiça Health Research Center (CISM), Manhiça, Mozambique
| | - Laurence Slutsker
- Malaria Branch, Division of Parasitic Diseases and Malaria, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.,PATH, Malaria and NTDs, Seattle, Washington, United States of America
| | - Michael Ramharter
- Department of Tropical Medicine, Bernhard Nocht Institute for Tropical Medicine & Dept. of Medicine University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Clara Menéndez
- ISGlobal, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain.,Consorcio de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,Manhiça Health Research Center (CISM), Manhiça, Mozambique
| | - Raquel González
- ISGlobal, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain.,Consorcio de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,Manhiça Health Research Center (CISM), Manhiça, Mozambique
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Ndiath MM, Cisse B, Ndiaye JL, Gomis JF, Bathiery O, Dia AT, Gaye O, Faye B. Application of geographically-weighted regression analysis to assess risk factors for malaria hotspots in Keur Soce health and demographic surveillance site. Malar J 2015; 14:463. [PMID: 26581562 PMCID: PMC4652414 DOI: 10.1186/s12936-015-0976-9] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Accepted: 10/28/2015] [Indexed: 12/01/2022] Open
Abstract
Background In Senegal, considerable efforts have been made to reduce malaria morbidity and mortality during the last decade. This resulted in a marked decrease of malaria cases. With the decline of malaria cases, transmission has become sparse in most Senegalese health districts. This study investigated malaria hotspots in Keur Soce sites by using geographically-weighted regression. Because of the occurrence of hotspots, spatial modelling of malaria cases could have a considerable effect in disease surveillance. Methods This study explored and analysed the spatial relationships between malaria occurrence and socio-economic and environmental factors in small communities in Keur Soce, Senegal, using 6 months passive surveillance. Geographically-weighted regression was used to explore the spatial variability of relationships between malaria incidence or persistence and the selected socio-economic, and human predictors. A model comparison of between ordinary least square and geographically-weighted regression was also explored. Vector dataset (spatial) of the study area by village levels and statistical data (non-spatial) on malaria confirmed cases, socio-economic status (bed net use), population data (size of the household) and environmental factors (temperature, rain fall) were used in this exploratory analysis. ArcMap 10.2 and Stata 11 were used to perform malaria hotspots analysis. Results From Jun to December, a total of 408 confirmed malaria cases were notified. The explanatory variables-household size, housing materials, sleeping rooms, sheep and distance to breeding site returned significant t values of −0.25, 2.3, 4.39, 1.25 and 2.36, respectively. The OLS global model revealed that it explained about 70 % (adjusted R2 = 0.70) of the variation in malaria occurrence with AIC = 756.23. The geographically-weighted regression of malaria hotspots resulted in coefficient intercept ranging from 1.89 to 6.22 with a median of 3.5. Large positive values are distributed mainly in the southeast of the district where hotspots are more accurate while low values are mainly found in the centre and in the north. Conclusion Geographically-weighted regression and OLS showed important risks factors of malaria hotspots in Keur Soce. The outputs of such models can be a useful tool to understand occurrence of malaria hotspots in Senegal. An understanding of geographical variation and determination of the core areas of the disease may provide an explanation regarding possible proximal and distal contributors to malaria elimination in Senegal.
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Affiliation(s)
- Mansour M Ndiath
- Service Parasitologie, Université Cheikh Anta Diop, Dakar, Senegal.
| | - Badara Cisse
- Service Parasitologie, Université Cheikh Anta Diop, Dakar, Senegal. .,London School of Hygiene and Tropical Medicine, London, UK.
| | | | - Jules F Gomis
- Service Parasitologie, Université Cheikh Anta Diop, Dakar, Senegal.
| | | | - Anta Tal Dia
- Institut de santé et de développement, UCAD, Dakar, Senegal.
| | - Oumar Gaye
- Service Parasitologie, Université Cheikh Anta Diop, Dakar, Senegal.
| | - Babacar Faye
- Service Parasitologie, Université Cheikh Anta Diop, Dakar, Senegal. .,Unité Mixte Internationale « Environnement, Santé, Sociétés » (UMI3189 ESS), CNRS-UCAD-CNRST-USTTB-UGB, Dakar, Senegal.
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