| Literature DB >> 35883064 |
T Druetz1,2,3, L van den Hoogen4, G Stresman5, V Joseph4,6, K E S Hamre7,8, C Fayette9, F Monestime9, J Presume10, I Romilus10, G Mondélus10, T Elismé10, S Cooper6, D Impoinvil7, R A Ashton4, E Rogier7, A Existe10, J Boncy10, M A Chang7, J F Lemoine11, C Drakeley5, T P Eisele4.
Abstract
INTRODUCTION: Serological methods provide useful metrics to estimate age-specific period prevalence in settings of low malaria transmission; however, evidence on the use of seropositivity as an endpoint remains scarce in studies to evaluate combinations of malaria control measures, especially in children. This study aims to evaluate the immediate effects of a targeted mass drug administration campaign (tMDA) in Haiti by using serological markers.Entities:
Keywords: Cohort study; Evaluation; Haiti; Impact assessment; Malaria; Mass drug administration; Serology; Seropositivity
Mesh:
Substances:
Year: 2022 PMID: 35883064 PMCID: PMC9321307 DOI: 10.1186/s12879-022-07616-8
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.667
Sociodemographic characteristics of the participants, by year and exposure group
| Control group | P valuea | tMDA group | P valuea | |||
|---|---|---|---|---|---|---|
| 2017 | 2018 | 2017 | 2018 | |||
| Number | 580 | 580 | 174 | 174 | ||
| Female | 0.45 | 0.52 | ||||
| Commune | ||||||
| Moron | 0.25 | 0.01 | ||||
| Chambellan | 0.25 | 0.04 | ||||
| Dame-Marie | 0.41 | 0.18 | ||||
| Anse-d’Hainault | 0.08 | 0.70 | ||||
| Les Irois | 0.01 | 0.07 | ||||
| Age (mean)b | 10.4 | 11.4 | < 0.001 | 11.3 | 12.3 | < 0.001 |
| Slept under a bed net the night before | 0.45 | 0.37 | 0.005 | 0.53 | 0.49 | 0.453 |
| History of fever (last 2 weeks) | 0.02 | 0.05 | 0.009 | 0.02 | 0.05 | 0.190 |
| RDT positive | 0.01 | 0.00 | 0.005 | 0.04 | 0.00 | 0.008 |
| Occupation of the head of the household | ||||||
| Farmer | 0.83 | 0.74 | < 0.001 | 0.78 | 0.76 | 0.064 |
| Shop keeper | 0.10 | 0.12 | 0.10 | 0.17 | ||
| Other | 0.07 | 0.01 | 0.12 | 0.07 | ||
| Large household (> 5 members) | 0.61 | 0.66 | 0.077 | 0.63 | 0.72 | 0.086 |
| Household owns ≥ 1 bed net | 0.53 | 0.53 | 0.076 | 0.62 | 0.70 | 0.142 |
| Household owns livestock | 0.62 | 0.73 | < 0.001 | 0.49 | 0.66 | 0.002 |
| Household received IRS (last 3 months) | 0 | 0.10 | < 0.001 | 0 | 0.58 | < 0.001 |
tMDA targeted mass drug administration, RDT rapid diagnostic test, IRS indoor residual spraying
aChi-2 test (or t-test for continuous variable) on within-group difference
bAge ranged 5–19 years old. Ranges were similar across groups
Fig. 1Box plots of normalized antibody concentration level for five P. falciparum antigens (2018 vs. 2017, by exposure group). Antibody concentration level is expressed by the median fluorescence intensity (MFI) after log-transformation and standardization between years for titre concentration. Mean concentration per year per group is displayed by red circles
Fig. 2Changes in seroprevalence for five P. falciparum antigens (2018 vs 2017, by exposure group). Seroprevalence was estimated by fitting multilevel logistic regression models, with adjustment for age, use of a bednet the night before, size of the household, occupation of the head of the household and possession of livestock. Robust variance estimators were used, and models used random intercepts at the individual, household and commune levels. The intervention group refer to the individuals who self-reported having received MDA in 2018, while the control group refer to individuals who self-report not being exposed to MDA in 2018. No participant was exposed to MDA in 2017, whatever the group
Fig. 3Treatment effects of MDA campaign on IgG seropositivity to five P. falciparum antigens. Treatment effects estimates are derived from multilevel logistic regression models, with adjustment for age, use of a bednet the night before, size of the household, occupation of the head of the household and possession of livestock. Robust variance estimators were used, and models used random intercepts at the individual, household and commune levels. Marginal probabilities were used for computing risk differences and relative risks. Treatment effect estimates are displayed with their 95% confidence intervals