Presentation_1_Accessibility of Early Infant Diagnostic Services by Under-5 Years and HIV Exposed Children in Muheza District, North-East Tanzania.PDF

<p>Introduction: Early infant diagnosis (EID) of Human Immunodeficiency Virus (HIV) provides an opportunity for follow up of HIV exposed children for early detection of infection and timely access to antiretroviral treatment. We assessed predictors for accessing HIV diagnostic services among under-five children exposed to HIV infection in Muheza district, Tanzania.</p><p>Methods: A cross sectional facility-based study among mother/guardian-child pairs of HIV exposed children was conducted from June 2015 to June 2016. Using a structured questionnaire, we collected information on HIV status, socio-demographic characteristics and other relevant data. Multiple regression analyses were used to investigate associations of potential predictors of accessing EID services.</p><p>Results: A total of 576 children with their respective mothers/guardians were recruited. Of the 576 mothers/guardians, 549 (95.3%) were the biological mothers with a median age of 34 years (inter-quartile range: 30–38 years). The median age of the 576 children was 15 months (inter- quartile range: 8.5–38.0 months). A total of 251 (43.6%) children were born to mothers with unknown HIV status at conception. Only 329 (57.1%) children accessed EID between 4 and 6 weeks of age. Children born to mothers with unknown HIV status at conception (AOR = 0.6, 95% CI 0.4–0.8) and those with ages 13–59 months (AOR = 0.4, 95% CI 0.2–0.6) were the significant predictors of missed opportunity to access EID. Children living with the head of household with at least a high education level had higher chances of accessing EID (AOR = 1.8, 95% CI 1.1–3.3). Their chances of accessing EID services was three-fold higher among mothers/guardians with good knowledge of HIV infection prevention of mother to child transmission (AOR = 3.2, 95% CI 2.0–5.2) than those with poor knowledge. Mothers/guardians living in rural areas had poorer knowledge of HIV infection prevention of mother to child transmission (AOR = 0.6, 95% CI 0.4–0.9) than those living in urban areas.</p><p>Conclusion: Accessibility of EID services among children below 5 years exposed to HIV infection in Muheza is low. These findings stress the need for continued HIV education and outreach services, particularly in rural areas in order to improve maternal and child health.</p

Additional file 1: Table S1. of Molecular epidemiological investigations of plague in Eastern Province of Zambia

Nucleotide sequences of pla gene of Y. pestis from this study. (DOCX 34 kb

Selection probabilities of households in bootstrapping.

Selection probabilities of households in bootstrapping.</p

Individual demographic characteristics of individuals enrolled in the original study and missed population study, adults 15 years and older.

The original serosurvey was carried out in April—June 2022 in Ndola and Choma districts, Zambia, using stratified multi-stage clustering design. The follow-up missed population study was carried out in a subset of clusters of the original survey between July—August 2022. This study was carried out in a subsample of clusters from the original survey; in each selected cluster, a sample of households not available during listing of the original serosurvey, and hence excluded from its sampling frame, were randomly selected. (DOCX)</p

Healthcare-seeking and characteristics reported by caregivers of children 1–4 years old and 5–14 years old.

Results presented are for univariable analysis, by district and age group, and multivariable analysis, by age group only. “Original” refers to the serosurvey carried out in April—June 2022 in Ndola and Choma districts, Zambia, using stratified multi-stage clustering design. “Missed” refers to the study sample from the follow-up missed population study, carried out in a subset of clusters of the original survey between July—August 2022. This study was carried out in a subsample of clusters from the original survey; in each selected cluster, a sample of households not available during listing of the original serosurvey, and hence excluded from its sampling frame, were randomly selected.</p

Status of households enrolled in the original community-based measles serological survey and missed populations study, Ndola and Choma Districts, Zambia, 2022.

A. The distribution of household status from listing in the original serosurvey conducted in Choma and Ndola Districts, by cluster. Households classified as “Available” provided consent to participate in the study and reported that they would be available during the data collection; these households comprised the sampling frame for the original study. Households that refused (“Refused”) were excluded from the original study sampling frame and were ineligible for the missed populations study. Households classified as “Non-contact” were households that were locked at the time of listing (and during revisits), or if there was no adult respondent at home, and nobody was available to provide information about the household (e.g. neighbor). Finally, households that were listed but which reported not being available during data collection (“Contact, not available”) were excluded from the sampling frame in the original study. The households in the latter two categories were eligible for the missed populations study. Clusters are arranged in descending order by percentage of households eligible for the missed populations study (“Non-contact” and “Contact, not available” households). “X”‘s indicate clusters selected for the missed population study. B. Distribution of households that the data collection team attempted to reach by status, cluster, and district in the missed populations study. Households classified as “Completed” were successfully located and provided consent to participate in the study. “Household not found” indicates households identified for inclusion in the missed populations study that could not be located during this study. “Non-contact” refers to households which were physically located, but ones in which the data collection team could not contact its occupants. No household refused participation. Clusters are arranged in order of decreasing percent missed in the missed populations study, comprised of “Household Not Found” and “Non-contact” households.</p

Covariates for predictive model for measles seropositivity.

Covariates for predictive model for measles seropositivity.</p

Comparison of household-level characteristics of individuals enrolled in the original community-based measles serological survey and missed population study.

The original serosurvey was carried out in April—June 2022 in Ndola and Choma districts, Zambia, using stratified multi-stage cluster design. The follow-up missed population study was carried out in a subset of clusters of the original survey between July—August 2022. This study was carried out in a subsample of clusters from the original survey; in each selected cluster, a sample of households not available during listing of the original serosurvey, and hence excluded from its sampling frame, were randomly selected.</p

Estimates of outcomes of interest using the sampling frame from the original community-based measles serological survey (excluding missed households) in Ndola and Choma Districts, Zambia, 2022, and a mixed sampling frame (including both households enrolled in the missed population study and households enrolled in the original study).

Weighting was done using the estimated population in each age group in each cluster in the missed population study for outcomes of interest including A. Healthcare seeking (actual and theoretical) at facilities of interest (Arthur Davison Children’s Hospital and Choma General Hospital for children 1–4 and 5–14 years old, and Ndola Teaching Hospital and Choma General Hospital for adults 15 years and older), B. MCV2 coverage, children 1–4 years old, and C. Measles seroprevalence, children 1–4 years old.</p

Number of households selected in each cluster in bootstrapping, by age group and district.

Number of households selected in each cluster in bootstrapping, by age group and district.</p