Multiplex IgG antibody response and malaria parasitemia among children ages 1-59 months in the MORDOR Niger trial, 2015-2018

We measured IgG responses to several malaria, bacterial, and protozoan pathogens using a multiplex bead assay in pre-specified substudy of 30 communities in the rural, MORDOR Niger placebo-controlled trial over a three-year period (n=5,642 blood specimens, n=3,814 children ages 1-59 months). We compared seroprevalence and serological force of infection between 15 communities that received biannual mass distribution of azithromycin versus placebo. The study included antigens to: Plasmodium falciparum (MSP-1, AMA1, GLURP-Ro, LSA1, CSP, HRP2), P. vivax (MSP-1), P. ovale (MSP-1), P. malariae (MSP-1), Campylobacter jejuni (p18, p39), enterotoxigenic Echerichia coli ( ETEC LTB), Vibrio cholerae (CTB), Salmonella enterica (LPS serogroups B, D), Cryptosporidium parvum (Cp17, Cp23), Giardia duodenalis (VSP-3, VSP-5), and Streptococcus group A (SPEB). Communities with 200 to 2,000 inhabitants based on the Niger 2012 census were eligible for inclusion in the trial, and children ages 1–59 months who weighed >3.8 kg were eligible for treatment. An intensive morbidity monitoring trial enrolled 30 communities and randomized them 1:1 to receive either biannual azithromycin or placebo to all children 1-59 months old (NCT02048007). The trial used a repeated cross-sectional design, whereby 40 children per community were randomly sampled in each measurement round and invited to participate in a monitoring visit. The trial’s open cohort design meant that children aged in and out of the study based on their age at the time of treatment. Field staff collected dried blood spots from participating children at baseline and annually thereafter at 12, 24, and 36 months of follow-up. The antibody substudy included a supplemental visit at 6 months, following the malaria season. Children who were randomly selected in multiple survey rounds contributed to longitudinal analyses. Dried blood spots were tested using a multiplex bead assay on the Luminex platform for IgG responses. Separate blood specimens were assessed by microscopy for malaria parasitemia. The associated manuscript includes specimen testing details. The study included antigens to: Plasmodium falciparum (MSP-1, AMA1, GLURP-Ro, LSA1, CSP, HRP2), P. vivax (MSP-1), P. ovale (MSP-1), P. malariae (MSP-1), Campylobacter jejuni (p18, p39), enterotoxigenic Escherichia coli ( ETEC LTB), Vibrio cholerae (CTB), Salmonella enterica (LPS serogroups B, D), Cryptosporidium parvum (Cp17, Cp23), Giardia duodenalis (VSP-3, VSP-5), and Streptococcus group A (SPEB). In addition to pathogens included in the analysis, the dataset additionally includes antibody responses to Chylamydia trachomatis (Pgp3, CT694) and Strongyloides stercoralis (NIE), which showed no evidence of seropositivity in this setting but have been included for completeness. This repository includes data that underlies the analyses in the manuscript entitled Biannual azithromycin distribution and antibody responses to malaria, bacterial, and protozoan pathogens among Nigerien children There are two datasets: mordor-ab-analysis-public.csv/.rds includes all antibody data in long format (unique observation is child-visit-antigen) mordor-ab-treatment-public.csv/.rds includes treatment status for all children 1-59 months in the 30 communities. There were more children (n=9,066) who were measured for treatment status than the random sample of up to 40 children per community who were enrolled in the antibody substudy in each visit. Full replication materials are cross-linked in the Open Science Framework (osf.io) and GitHub (proctor-ucsf/mordor-antibody). To replicate the study's analysis, we recommend these steps. (1) Clone the GitHub repository to your local drive (mordor-antibody); (2) download the datasets from Dryad (here) or OSF; (3) create a mordor-antibody/data subdirectory and copy the two datasets (.csv / .rds) into it; (4) finally, create a mordor-antibody/figures subdirectory to store output. All of the analysis scripts should run smoothly. The first two data processing scripts will not run because they read in our internal datasets with PII. We have included them for transparency and completeness. Should you have any questions about the files in this repository, please contact Ben Arnold at UCSF (ben.arnold@ucsf.edu).