1. How does gravidity affect malaria correlation?
Gravidity, or the number of pregnancies a woman has had, can impact the correlation between malaria burden in pregnant women and children. Studies have shown that there is less difference between women and children when restricting the analysis to primigravidae, or women who are pregnant for the first time. However, the effect of gravidity and other factors such as HIV were not consistently assessed in previous studies. Therefore, a better understanding of the validity of ANC prevalence data for monitoring transmission in the community and the factors that affect this relationship remains to be developed. New surveillance tools, such as antibodies against the pregnancy-specific antigen VAR2CSA, can potentially increase sensitivity to detect recent exposure in low-transmission settings where detecting a sufficient number of active infections to estimate trends in burden is difficult. Combined with novel clustering approaches, ANC data can increase the resolution to detect spatial patterns, providing a cost-effective approach to target interventions to the most affected areas. In this study, the correlation between malaria burden at first ANC visits and data from cross-sectional surveys and clinical cases in three settings in southern Mozambique with different transmission levels is estimated and compared. The effect of HIV and gravidity on the correlation is characterized, and the added value of antibody data obtained from a bead-based multiplex immunoassay against VAR2CSA and general malaria antigens, as well as a newly developed hotspot detection algorithm, is assessed to improve surveillance in malaria-endemic areas.
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2. What is the correlation between P. falciparum parasite rates using qPCR and PfPR RDT in pregnant women and children?
The correlation between P. falciparum parasite rates using qPCR and PfPR RDT in pregnant women and children shows lower correlations and weaker linear relationships. At RDT-detection levels, the Pearson correlation coefficient (PCC) is lower, with values ranging from 0.61 to 0.94. The linear regression slope is not consistent with equality, ranging from 0.17 to 0.97. However, in low-transmission areas like Magude and Manhica, good consistency of both PfPR qPCR and PfPR RDT between multigravid pregnant women and children was observed, regardless of HIV status.
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3. What is the decline in PfPR qPCR in pregnant women during the study?
The decline in PfPR qPCR in pregnant women during the study was from 10.7% to 4.1%, representing an overall decline of 62% (65%, 58%, and 62% in Magude, Ilha Josina, and Manhica, respectively, with a p-value of less than 0.001). This decline was consistent across all three locations and correlated with a delay of approximately 90 days, regardless of gravidity. The correlation between clinical cases and ANC data collected around 90 days after the clinical cases was the strongest, with a Pearson's correlation coefficient (PCC) of 0.87 (95% CI 0.69-0.91). Similar results were observed at RDT-detection levels, with a PCC greater than 0.78 (95% CI 0.27-0.85) and shorter time lags of around 40 days when including multigravida women. HIV status did not significantly impact these estimates.
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4. What is the study area and population?
The study was conducted in Manhica and Magude districts in Maputo Province, southern Mozambique, between November 2016 and November 2019. The population consisted of 8,745 pregnant women residing in the study area, attending their first ANC visit at Manhica District Hospital, Ilha Josina Health Centre, or Magude Health Centre. Additionally, data from 15,467 children under 5 years old attending the three health facilities, 37,131 RDT and microscopy results from children under 5 years attending health facilities, and 3,933 children aged 2-10 years from age-stratified cross-sectional surveys were collected. The population was evenly represented with 50.3% female and 49.2% male, with 0.5% unavailable information. Geolocalisation of the residence of pregnant women and children was obtained from a local health and demographic surveillance system using their permanent or family identification number.
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