Lifetime risk of maternal near miss morbidity: a novel indicator of maternal health.

BACKGROUND: The lifetime risk of maternal death quantifies the probability that a 15-year-old girl will die of a maternal cause in her reproductive lifetime. Its intuitive appeal means it is a widely used summary measure for advocacy and international comparisons of maternal health. However, relative to mortality, women are at an even higher risk of experiencing life-threatening maternal morbidity called 'maternal near miss' (MNM) events-complications so severe that women almost die. As maternal mortality continues to decline, health indicators that include information on both fatal and non-fatal maternal outcomes are required. METHODS: We propose a novel measure-the lifetime risk of MNM-to estimate the cumulative risk that a 15-year-old girl will experience a MNM in her reproductive lifetime, accounting for mortality between the ages 15 and 49 years. We apply the method to the case of Namibia (2019) using estimates of fertility and survival from the United Nations World Population Prospects along with nationally representative data on the MNM ratio. RESULTS: We estimate a lifetime risk of MNM in Namibia in 2019 of between 1 in 40 and 1 in 35 when age-disaggregated MNM data are used, and 1 in 38 when a summary estimate for ages 15-49 years is used. This compares to a lifetime risk of maternal death of 1 in 142 and yields a lifetime risk of severe maternal outcome (MNM or death) of 1 in 30. CONCLUSIONS: The lifetime risk of MNM is an urgently needed indicator of maternal morbidity because existing measures (the MNM ratio or rate) do not capture the cumulative risk over the reproductive life course, accounting for fertility and mortality levels.

Pregnancy-related mortality up to 1 year postpartum in sub-Saharan Africa: an analysis of verbal autopsy data from six countries.

OBJECTIVE: To compare the causes of death for women who died during pregnancy and within the first 42 days postpartum with those of women who died between >42 days and within 1 year postpartum. DESIGN: Open population cohort (Health and Demographic Surveillance Systems). SETTING: Ten Health and Demographic Surveillance Systems (HDSS) in The Gambia, Kenya, Malawi, Tanzania, Ethiopia and South Africa. POPULATION: 2114 deaths which occurred within 1 year of the end of pregnancy where a verbal autopsy interview was conducted from 2000 to 2019. METHODS: InterVA5 and InSilicoVA verbal autopsy algorithms were used to attribute the most likely underlying cause of death, which were grouped according to adapted International Classification of Diseases-Maternal Mortality categories. Multinomial regression was used to compare differences in causes of deaths within 42 days versus 43-365 days postpartum adjusting for HDSS and time period (2000-2009 and 2010-2019). MAIN OUTCOME MEASURES: Cause of death and the verbal autopsy Circumstances of Mortality Categories (COMCATs). RESULTS: Of 2114 deaths, 1212 deaths occurred within 42 days postpartum and 902 between 43 and 365 days postpartum. Compared with deaths within 42 days, deaths from HIV and TB, other infectious diseases, and non-communicable diseases constituted a significantly larger proportion of late pregnancy-related deaths beyond 42 days postpartum, and health system failures were important in the circumstances of those deaths. The contribution of HIV and TB to deaths beyond 42 days postpartum was greatest in Southern Africa. The causes of pregnancy-related mortality within and beyond 42 days postpartum did not change significantly between 2000-2009 and 2010-2019. CONCLUSIONS: Cause of death data from the extended postpartum period are critical to inform prevention. The dominance of HIV and TB, other infectious and non-communicable diseases to (late) pregnancy-related mortality highlights the need for better integration of non-obstetric care with ante-, intra- and postpartum care in high-burden settings.

Measuring under-5 mortality and fertility through mobile phone surveys: an assessment of selection bias in 34 low-income and middle-income countries.

OBJECTIVES: This study aims to assess sample selection bias in mobile phone survey estimates of fertility and under-5 mortality. DESIGN: With data from the Demographic and Health Surveys, we use logistic regressions to identify sociodemographic correlates of mobile phone ownership and access, and Poisson regressions to estimate the association between mobile phone ownership (or access) and fertility and under-5 mortality estimates. We evaluate the potential reasons why estimates by mobile phone ownership differ using a set of behavioural characteristics. SETTING: 34 low-income and middle-income countries, mostly in sub-Saharan Africa. PARTICIPANTS: 534 536 women between the ages of 15 and 49. OUTCOME MEASURES: Under-5 mortality rate (U5MR) and total fertility rate (TFR). RESULTS: Mobile phone ownership ranges from 23.6% in Burundi to 96.7% in Armenia. The median TFR ratio and U5MR ratio between the non-owners and the owners of a mobile phone are 1.48 and 1.29, respectively. Fertility and mortality rates would be biased downwards if estimates are only based on women who own or have access to mobile phones. Estimates of U5MR can be adjusted through poststratification using age, educational level, area of residence, wealth and marital status as weights. However, estimates of TFR remain biased even after adjusting for these covariates. This difference is associated with behavioural factors (eg, contraceptive use) that are not captured by the poststratification variables, but for which there are also differences between mobile phone owners and non-owners. CONCLUSIONS: Mobile phone surveys need to collect data on sociodemographic background characteristics to be able to weight and adjust mortality estimates ex post facto. Fertility estimates from mobile phone surveys will be biased unless further research uncovers the mechanisms driving the bias.

An evaluation of truncated birth histories for the rapid measurement of fertility and child survival.

BACKGROUND: Full birth histories (FBHs) are a key tool for estimating fertility and child mortality in low- and middle-income countries, but they are lengthy to collect. This is not desirable, especially for rapid turnaround surveys that ought to be short (e.g., mobile phone surveys). To reduce the length of the interview, some surveys resort to truncated birth histories (TBHs), where questions are asked only on recent births. METHODS: We used 32 Malaria Indicator Surveys that included TBHs from 18 countries in sub-Saharan Africa. Each set of TBHs was paired and compared to an overlapping set of FBHs (typically from a standard Demographic and Health Survey). We conducted a variety of data checks, including a comparison of the proportion of children reported in the reference period and a comparison of the fertility and mortality estimates. RESULTS: Fertility and mortality estimates from TBHs are lower than those based on FBHs. These differences are driven by the omission of events and the displacement of births backward and out of the reference period. CONCLUSIONS: TBHs are prone to misreporting errors that will bias both fertility and mortality estimates. While we find a few significant associations between outcomes measured and interviewer's characteristics, data quality markers correlate more consistently with respondent attributes, suggesting that truncation creates confusion among mothers being interviewed. Rigorous data quality checks should be put in place when collecting data through this instrument in future surveys.

Comparison of programmatic data from antenatal clinics with population-based HIV prevalence estimates in the era of universal test and treat in western Kenya.

OBJECTIVE: To compare HIV prevalence estimates from routine programme data in antenatal care (ANC) clinics in western Kenya with HIV prevalence estimates in a general population sample in the era of universal test and treat (UTT). METHODS: The study was conducted in the area covered by the Siaya Health Demographic Surveillance System (Siaya HDSS) in western Kenya and used data from ANC clinics and the general population. ANC data (n = 1,724) were collected in 2018 from 13 clinics located within the HDSS. The general population was a random sample of women of reproductive age (15-49) who reside in the Siaya HDSS and participated in an HIV sero-prevalence survey in 2018 (n = 2,019). Total and age-specific HIV prevalence estimates were produced from both datasets and demographic decomposition methods were used to quantify the contribution of the differences in age distributions and age-specific HIV prevalence to the total HIV prevalence estimates. RESULTS: Total HIV prevalence was 18.0% (95% CI 16.3-19.9%) in the ANC population compared with 18.4% (95% CI 16.8-20.2%) in the general population sample. At most ages, HIV prevalence was higher in the ANC population than in the general population. The age distribution of the ANC population was younger than that of the general population, and because HIV prevalence increases with age, this reduced the total HIV prevalence among ANC attendees relative to prevalence standardised to the general population age distribution. CONCLUSION: In the era of UTT, total HIV prevalence among ANC attendees and the general population were comparable, but age-specific HIV prevalence was higher in the ANC population in most age groups. The expansion of treatment may have led to changes in both the fertility of women living with HIV and their use of ANC services, and our results lend support to the assertion that the relationship between ANC and general population HIV prevalence estimates are highly dynamic.

Women's risk of death beyond 42 days post partum: a pooled analysis of longitudinal Health and Demographic Surveillance System data in sub-Saharan Africa.

BACKGROUND: WHO's standard definitions of pregnancy-related and maternal deaths only include deaths that occur within 42 days of delivery, termination, or abortion, with major implications for post-partum care and maternal mortality surveillance. We therefore estimated post-partum survival from childbirth up to 1 year post partum to evaluate the empirical justification for the 42-day post-partum threshold. METHODS: We used prospective, longitudinal Health and Demographic Surveillance System (HDSS) data from 30 sites across 12 sub-Saharan African countries to estimate women's risk of death from childbirth until 1 year post partum from all causes. Observations were included if the childbirth occurred from 1991 onwards in the HDSS site and maternal age was 10-54 years. We calculated person-years as the time between childbirth and next birth, outmigration, death, or the end of the first year post partum, whichever occurred first. For six post-partum risk intervals (0-1 days, 2-6 days, 7-13 days, 14-41 days, 42-122 days, and 4-11 months), we calculated the adjusted rate ratios of death relative to a baseline risk of 12-17 months post partum. FINDINGS: Between Jan 1, 1991, and Feb 24, 2020, 647 104 births occurred in the HDSS sites, contributing to 602 170 person-years of exposure time and 1967 deaths within 1 year of delivery. After adjustment for confounding, mortality was 38·82 (95% CI 33·21-45·29) times higher than baseline on days 0-1 after childbirth, 4·97 (3·94-6·21) times higher for days 2-6, 3·35 (2·64-4·20) times higher for days 7-13, and 2·06 (1·74-2·44) times higher for days 14-41. From 42 days to 4 months post partum, mortality was still 1·20 (1·03-1·39) times higher (ie, a 20% higher risk), but deaths in this interval would be excluded from measurement of pregnancy-related mortality. Extending the WHO 42-day post-partum threshold up to 4 months would increase the post-partum pregnancy-related mortality ratio by 40%. INTERPRETATION: This multicountry study has implications for measurement and clinical practice. It makes the case for WHO to extend the 42-day post-partum threshold to capture the full duration of risk of pregnancy-related deaths. There is a need for a new indicator to track late pregnancy-related deaths that occur beyond 42 days, which are otherwise excluded from global maternal health surveillance efforts. Our results also emphasise the need for international agencies to disaggregate estimates by antepartum, intrapartum, postpartum, and extended post-partum periods. Additionally, the schedule and content of postnatal care packages should reflect the extended duration of post-partum risk. FUNDING: The UK Economic and Social Research Council.

Divergent age patterns of under-5 mortality in south Asia and sub-Saharan Africa: a modelling study.

BACKGROUND: Understanding the age pattern of under-5 mortality is essential for identifying the most vulnerable ages and underlying causes of death, and for assessing why the decline in child mortality is slower in some countries and subnational areas than others. The aim of this study is to detect age patterns of under-5 mortality that are specific to low-income and middle-income countries (LMICs). METHODS: In this modelling study, we used data from 277 Demographic and Health Surveys (DHSs), 58 Health and Demographic Surveillance Systems (HDSSs), two cohort studies, and two sample-registration systems. From these sources, we collected child date of birth and date of death (or age at death) from LMICs between 1966 and 2020. We computed 22 deaths rates from each survey with the following age breakdowns: 0, 7, 14, 21, and 28 days; 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 18, and 21 months; and 2, 3, 4, and 5 years. We assessed how probabilities of dying estimated for the 22 age groups deviated from predictions generated by a vital registration model that reflects the historical mortality of 25 high-income countries. FINDINGS: We calculated mortality rates of 81 LMICs between 1966 and 2020. In contrast with the other regions of the world, we found that under-5 mortality in south Asia and sub-Saharan Africa was characterised by increased mortality at both ends of the age range (ie, younger than 28 days and older than 6 months) at a given level of mortality. Observed mortality in these regions was up to 2 times higher than predicted by the vital registration model for the younger-than-28 days age bracket, and up to 10 times higher than predicted for the older-than-6 months age bracket. This age pattern of under-5 mortality is significant in 17 countries in south Asia and sub-Saharan Africa. Excess mortality in children older than 6 months without excess mortality in children younger than 28 days was found in 38 countries. In south Asia, results were consistent across data sources. In sub-Saharan Africa, excess mortality in children younger than 28 days was found mostly in DHSs; the majority of HDSSs did not show this excess mortality. We have attributed this difference in data sources mainly to omissions of early deaths in HDSSs. INTERPRETATION: In countries with age patterns of under-5 mortality that diverge from predictions, evidence-based public health interventions should focus on the causes of excess of mortality; notably, the effect of fetal growth restriction and infectious diseases. The age pattern of under-5 mortality will be instrumental in assessing progress towards the decline of under-5 mortality and the Sustainable Development Goals. FUNDING: Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health.

Assessment of the consistency of health and demographic surveillance and household survey data: A demonstration at two HDSS sites in The Gambia.

OBJECTIVE: To assess whether an adapted Demographic and Health Survey (DHS) like cross-sectional household survey with full pregnancy histories can demonstrate the validity of health and demographic surveillance (HDSS) data by producing similar population structural characteristics and childhood mortality indicators at two HDSS sites in The Gambia-Farafenni and Basse. METHODS: A DHS-type survey was conducted of 2,580 households in the Farafenni HDSS, and 2,907 in the Basse HDSS. Household members were listed and pregnancy histories obtained for all women aged 15-49. HDSS datasets were extracted for the same households including residency episodes for all current and former members and compared with the survey data. Neonatal (0-28 days), infant (<1 year), child (1-4 years) and under-5 (< 5 years) mortality rates were derived from each source by site and five-year periods from 2001-2015 and by calendar year between 2011 and 2015 using Kaplan-Meier failure probabilities. Survey-HDSS rate ratios were determined using the Mantel-Haenszel method. RESULTS: The selected households in Farafenni comprised a total population of 27,646 in the HDSS, compared to 26,109 captured in the household survey, implying higher coverage of 94.4% (95% CI: 94.1-94.7; p<0.0001) against a hypothesised proportion of 90% in the HDSS. All population subgroups were equally covered by the HDSS except for the Wollof ethnic group. In Basse, the total HDSS population was 49,287, compared to 43,538 enumerated in the survey, representing an undercount of the HDSS by the survey with a coverage of 88.3% (95% CI: 88.0-88.6; p = 1). All sub-population groups were also under-represented by the survey. Except for the neonatal mortality rate for Farafenni, the childhood mortality indicators derived from pregnancy histories and HDSS data compare reasonably well by 5-year periods from 2001-2015. Annual estimates from the two data sources for the most recent quinquennium, 2011-2015, were similar in both sites, except for an excessively high neonatal mortality rate for Farafenni in 2015. CONCLUSION: Overall, the adapted DHS-type survey has reasonably represented the Farafenni HDSS database using population size and structure; and both databases using childhood mortality indicators. If the hypothetical proportion is lowered to 85%, the survey would adequately validate both HDSS databases in all considered aspects. The adapted DHS-type sample household survey therefore has potential for validation of HDSS data.

Evaluating pregnancy reporting in Siaya Health and Demographic Surveillance System through record linkage with ANC clinics.

Introduction: Health and Demographic Surveillance Systems (HDSS) are important sources of population health data in sub-Saharan Africa, but the recording of pregnancies, pregnancy outcomes, and early mortality is often incomplete. Objective: This study assessed HDSS pregnancy reporting completeness and identified predictors of unreported pregnancies that likely ended in adverse outcomes. Methods: The analysis utilized individually-linked HDSS and antenatal care (ANC) data from Siaya, Kenya for pregnancies in 2018-2020. We cross-checked ANC records with HDSS pregnancy registrations and outcomes. Pregnancies observed in the ANC that were missing reports in the HDSS despite a data collection round following the expected delivery date were identified as likely adverse outcomes, and we investigated the characteristics of such individuals. Clinical data were used to investigate the timing of HDSS pregnancy registration relative to care seeking and gestational age, and examine misclassification of miscarriages and stillbirths. Results: From an analytical sample of 2,475 pregnancies observed in the ANC registers, 46% had pregnancy registrations in the HDSS, and 89% had retrospectively reported pregnancy outcomes. 1% of registered pregnancies were missing outcomes, compared to 10% of those lacking registration. Registered pregnancies had higher rates of stillbirth and perinatal mortality than those lacking registration. In 77% of cases, women accessed ANC prior to registering the pregnancy in the HDSS. Half of reported miscarriages were misclassified stillbirths. We identified 141 unreported pregnancies that likely ended in adverse outcomes. Such cases were more common among those who visited ANC clinics during the first trimester, made fewer overall visits, were HIV-positive, and outside of formal union. Conclusions: Record linkage with ANC clinics revealed pregnancy underreporting in HDSS, resulting in biased measurement of perinatal mortality. Integrating records of ANC usage into routine data collection can augment HDSS pregnancy surveillance and improve monitoring of adverse pregnancy outcomes and early mortality.

Investigating clinic transfers among HIV patients considered lost to follow-up to improve understanding of the HIV care cascade: Findings from a cohort study in rural north-eastern South Africa.

Investigating clinical transfers of HIV patients is important for accurate estimates of retention and informing interventions to support patients. We investigate transfers for adults reported as lost to follow-up (LTFU) from eight HIV care facilities in the Agincourt health and demographic surveillance system (HDSS), South Africa. Using linked clinic and HDSS records, outcomes of adults more than 90 days late for their last scheduled clinic visit were determined through clinic and routine tracing record reviews, HDSS data, and supplementary tracing. Factors associated with transferring to another clinic were determined through Cox regression models. Transfers were graphically and geospatially visualised. Transfers were more common for women, patients living further from the clinic, and patients with higher baseline CD4 cell counts. Transfers to clinics within the HDSS were more likely to be undocumented and were significantly more likely for women pregnant at ART initiation. Transfers outside the HDSS clustered around economic hubs. Patients transferring to health facilities within the HDSS may be shopping for better care, whereas those who transfer out of the HDSS may be migrating for work. Treatment programmes should facilitate transfer processes for patients, ensure continuity of care among those migrating, and improve tracking of undocumented transfers.

Collecting mortality data via mobile phone surveys: A non-inferiority randomized trial in Malawi.

Despite the urgent need for timely mortality data in low-income and lower-middle-income countries, mobile phone surveys rarely include questions about recent deaths. Such questions might a) be too sensitive, b) take too long to ask and/or c) generate unreliable data. We assessed the feasibility of mortality data collection using mobile phone surveys in Malawi. We conducted a non-inferiority trial among a random sample of mobile phone users. Participants were allocated to an interview about their recent economic activity or recent deaths in their family. In the group that was asked mortality-related questions, half of the respondents completed an abridged questionnaire, focused on information necessary to calculate recent mortality rates, whereas the other half completed an extended questionnaire that also included questions about symptoms and healthcare. The primary trial outcome was the cooperation rate, i.e., the number of completed interviews divided by the number of mobile subscribers invited to participate. Secondary outcomes included self-reports of negative feelings and stated intentions to participate in future interviews. We called more than 7,000 unique numbers and reached 3,054 mobile subscribers. In total, 1,683 mobile users were invited to participate. The difference in cooperation rates between those asked to complete a mortality-related interview and those asked to answer questions about economic activity was 0.9 percentage points (95% CI = -2.3, 4.1), which satisfied the non-inferiority criterion. The mortality questionnaire was non-inferior to the economic questionnaire on all secondary outcomes. Collecting mortality data required 2 to 4 additional minutes per reported death, depending on the inclusion of questions about symptoms and healthcare. More than half of recent deaths elicited during mobile phone interviews had not been registered with the National Registration Bureau. Including mortality-related questions in mobile phone surveys is feasible. It might help strengthen the surveillance of mortality in countries with deficient civil registration systems. Registration: AEA RCT Registry, #0008065 (14 September 2021).

Patterns of engagement in HIV care during pregnancy and breastfeeding: findings from a cohort study in North-Eastern South Africa.

BACKGROUND: Eliminating mother-to-child transmission of HIV (MTCT) in sub-Saharan Africa is hindered by limited understanding of HIV-testing and HIV-care engagement among pregnant and breastfeeding women. METHODS: We investigated HIV-testing and HIV-care engagement during pregnancy and breastfeeding from 2014 to 2018 in the Agincourt Health and Demographic Surveillance System (HDSS). We linked HIV patient clinic records to HDSS pregnancy data. We modelled time to a first recorded HIV-diagnosis following conception, and time to antiretroviral therapy (ART) initiation following diagnosis using Kaplan-Meier methods. We performed sequence and cluster analyses for all pregnancies linked to HIV-related clinic data to categorise MTCT risk period engagement patterns and identified factors associated with different engagement patterns using logistic regression. We determined factors associated with ART resumption for women who were lost to follow-up (LTFU) using Cox regression. RESULTS: Since 2014, 15% of 10,735 pregnancies were recorded as occurring to previously (51%) or newly (49%) HIV-diagnosed women. New diagnoses increased until 2016 and then declined. We identified four MTCT risk period engagement patterns (i) early ART/stable care (51.9%), (ii) early ART/unstable care (34.1%), (iii) late ART initiators (7.6%), and (iv) postnatal seroconversion/early, stable ART (6.4%). Year of delivery, mother's age, marital status, and baseline CD4 were associated with these patterns. A new pregnancy increased the likelihood of treatment resumption following LTFU. CONCLUSION: Almost half of all pregnant women did not have optimal ART coverage during the MTCT risk period. Programmes need to focus on improving retention, and leveraging new pregnancies to re-engage HIV-positive women on ART.

Age patterns of HIV incidence in eastern and southern Africa: a modelling analysis of observational population-based cohort studies.

BACKGROUND: As the HIV epidemic in sub-Saharan Africa matures, evidence about the age distribution of new HIV infections and how this distribution has changed over the epidemic is needed to guide HIV prevention. We aimed to assess trends in age-specific HIV incidence in six population-based cohort studies in eastern and southern Africa, reporting changes in mean age at infection, age distribution of new infections, and birth cohort cumulative incidence. METHODS: We used a Bayesian model to reconstruct age-specific HIV incidence from repeated observations of individuals' HIV serostatus and survival collected among population HIV cohorts in rural Malawi, South Africa, Tanzania, Uganda, and Zimbabwe, in a collaborative analysis of the ALPHA network. We modelled HIV incidence rates by age, time, and sex using smoothing splines functions. We estimated incidence trends separately by sex and study. We used estimated incidence and prevalence results for 2000-17, standardised to study population distribution, to estimate mean age at infection and proportion of new infections by age. We also estimated cumulative incidence (lifetime risk of infection) by birth cohort. FINDINGS: Age-specific incidence declined at all ages, although the timing and pattern of decline varied by study. The mean age at infection was higher in men (cohort mean 27·8-34·6 years) than in women (24·8-29·6 years). Between 2000 and 2017, the mean age at infection per cohort increased slightly: 0·5 to 2·8 years among men and -0·2 to 2·5 years among women. Across studies, between 38% and 63% (cohort medians) of the infections in women were among those aged 15-24 years and between 30% and 63% of infections in men were in those aged 20-29 years. Lifetime risk of HIV declined for successive birth cohorts. INTERPRETATION: HIV incidence declined in all age groups and shifted slightly to older ages. Disproportionate new HIV infections occur among women aged 15-24 years and men aged 20-29 years, supporting focused prevention in these groups. However, 40-60% of infections were outside these ages, emphasising the importance of providing appropriate HIV prevention to adults of all ages. FUNDING: Bill & Melinda Gates Foundation.

Experiences and lessons learned from the real-world implementation of an HIV recent infection testing algorithm in three routine service-delivery settings in Kenya and Zimbabwe.

INTRODUCTION: Testing for recent HIV infection can distinguish recently acquired infection from long-standing infections. Given current interest in the implementation of recent infection testing algorithms (RITA), we report our experiences in implementing a RITA in three pilot studies and highlight important issues to consider when conducting recency testing in routine settings. METHODS: We applied a RITA, incorporating a limited antigen (LAg) avidity assay, in different routine HIV service-delivery settings in 2018: antenatal care clinics in Siaya County, Kenya, HIV testing and counselling facilities in Nairobi, Kenya, and female sex workers clinics in Zimbabwe. Discussions were conducted with study coordinators, laboratory leads, and facility-based stakeholders to evaluate experiences and lessons learned in relation to implementing recency testing. RESULTS: In Siaya County 10/426 (2.3%) of women testing HIV positive were classified as recent, compared to 46/530 (8.7%) of women and men in Nairobi and 33/313 (10.5%) of female sex workers in Zimbabwe. Across the study setting, we observed differences in acceptance, transport and storage of dried blood spot (DBS) or venous blood samples. For example, the acceptance rate when testing venous blood was 11% lower than when using DBS. Integrating our study into existing services ensured a quick start of the study and kept the amount of additional resources required low. From a laboratory perspective, the LAg avidity assay was initially difficult to operationalise, but developing a network of laboratories and experts to work together helped to improve this. A challenge that was not overcome was the returning of RITA test results to clients. This was due to delays in laboratory testing, the need for multiple test results to satisfy the RITA, difficulties in aligning clinic visits, and participants opting not to return for test results. CONCLUSION: We completed three pilot studies using HIV recency testing based on a RITA in Kenya and Zimbabwe. The main lessons we learned were related to sample collection and handling, LAg avidity assay performance, integration into existing services and returning of test results to participants. Our real-world experience could provide helpful guidance to people currently working on the implementation of HIV recency testing in sub-Saharan Africa.

Age patterns of under-5 mortality in sub-Saharan Africa during 1990-2018: A comparison of estimates from demographic surveillance with full birth histories and the historic record.

BACKGROUND: Estimates of under-5 mortality (U5M) for sub-Saharan African populations often rely heavily on full birth histories (FBHs) collected in surveys and model age patterns of mortality calibrated against vital statistics from other populations. Health and Demographic Surveillance Systems (HDSSs) are alternate sources of population-based data in much of sub-Saharan Africa, which are less formally utilized in estimation. OBJECTIVE: In this study we compare the age pattern of U5M in different African data sources (HDSSs, Demographic and Health Surveys (DHS), and Multiple Indicator Cluster Surveys (MICS)), and contrast these with the historical record as summarized in the Human Mortality Database and model age patterns. METHODS: We examined the relative levels of neonatal, postneonatal, infant, and child mortality across data sources. We directly compared estimates for DHS and MICS subnational regions with HDSS, and used linear regression to identify data and contextual attributes that correlated with the disparity between estimates. RESULTS: HDSS and FBH data suggests that African populations have higher levels of child mortality and lower infant mortality than the historic record. This age pattern is most explicit for Western African populations, but also characterizes data for other subregions. The comparison between HDSS and FBH data suggests that FBH estimates of child mortality are biased downward. The comparison is less conclusive for neonatal and infant mortality. CONTRIBUTION: This study questions the practice of using model age patterns derived from largely high-income settings for inferring or correcting U5M estimates for African populations. It also highlights the considerable uncertainty around the consistency of HDSS and FBH estimates of U5M.

Pregnancy Surveillance Methods within Health and Demographic Surveillance Systems.

Background: Pregnancy identification and follow-up surveillance can enhance the reporting of pregnancy outcomes, including stillbirths and perinatal and early postnatal mortality. This paper reviews pregnancy surveillance methods used in Health and Demographic Surveillance Systems (HDSSs) in low- and middle-income countries. Methods: We searched articles containing information about pregnancy identification methods used in HDSSs published between January 2002 and October 2019 using PubMed and Google Scholar. A total of 37 articles were included through literature review and 22 additional articles were identified via manual search of references. We reviewed the gray literature, including websites, online reports, data collection instruments, and HDSS protocols from the Child Health and Mortality Prevention Study (CHAMPS) Network and the International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH). In total, we reviewed information from 52 HDSSs described in 67 sources. Results: Substantial variability exists in pregnancy surveillance approaches across the 52 HDSSs, and surveillance methods are not always clearly documented. 42% of HDSSs applied restrictions based on residency duration to identify who should be included in surveillance. Most commonly, eligible individuals resided in the demographic surveillance area (DSA) for at least three months. 44% of the HDSSs restricted eligibility for pregnancy surveillance based on a woman's age, with most only monitoring women 15-49 years. 10% had eligibility criteria based on marital status, while 11% explicitly included unmarried women in pregnancy surveillance. 38% allowed proxy respondents to answer questions about a woman's pregnancy status in her absence. 20% of HDSSs supplemented pregnancy surveillance with investigations by community health workers or key informants and by linking HDSS data with data from antenatal clinics. Conclusions: Methodological guidelines for conducting pregnancy surveillance should be clearly documented and meticulously implemented, as they can have implications for data quality and accurately informing maternal and child health programs.

'If the results are negative, they motivate us'. Experiences of early infant diagnosis of HIV and engagement in Option B.

Few studies have explored the relationship between early infant diagnosis (EID) of HIV and mothers' engagement in care under Option B+. We conducted in-depth interviews with 20 women who initiated antiretroviral therapy (ART) under Option B+ in rural South Africa to explore the interactions between EID and maternal care engagement. Drawing on practice theory, we identified themes relating to Option B+ care engagement and EID. Women's practice of engagement with HIV care shaped their decision-making around EID. Mothers who disengaged from care during pregnancy were less inclined to utilise EID as they lacked information about its availability and benefits. For some mothers, tensions between wanting to breastfeed and perceptions that it could facilitate transmission led to repeated utilisation of EID as reassurance that the child remained negative. Some mothers used their child's negative result as a proxy for their status, subsequently disengaging from care. For some participants, an HIV diagnosis of their infant and the subsequent double burden of treatment visits for themselves and their infant, contributed to their disengagement. Women's care-seeking practices for themselves and their infants work in a symbiotic ecosystem and should be viewed interdependently to tailor interventions to improve EID uptake and Option B+ care engagement.

The impact of HIV status on the distance traveled to health facilities and adherence to care. A record-linkage study from rural South Africa.

BACKGROUND: For people living with HIV (PLWH), the burden of travelling to a clinic outside of one's home community in order to reduce the level of stigma experienced, may impact adherence to treatment and accelerate disease progression. METHODS: This study is set in the Agincourt Health and Demographic Surveillance System (HDSS) in South Africa. Probabilistic and interactive methods were used to individually link HDSS data with medical records. A regression analysis was used to assess whether travel distance was correlated with the condition for which individuals were seeking care (primarily HIV, diabetes or hypertension). For PLWH, a Cox proportional hazard regression model was used to test for an association between the distance travelled to the clinic and late attendance at follow-up visits. RESULTS: The adjusted relative risk (RR) of travelling to a clinic more than 5 km from that nearest to their home for HIV patients compared to those being treated for other conditions was 2.78 (95% confidence interval (CI) = 2.23-3.48). The adjusted Cox regression model showed no evidence for an association between the distance travelled to a clinic and the rate of late visits. (RR = 1.00, 95% CI = 0.99-1.00). CONCLUSIONS: The findings were consistent with the hypothesis that people living with HIV/AIDS would be willing to accept the burden of increased clinic travel distances in order to maintain anonymity and so limit their exposure to stigma from fellow community members. For those seeking HIV care the lack of an association between increased travel distances and late visit attendance suggests this may not impact treatment outcomes.

Can HIV recent infection surveillance help us better understand where primary prevention efforts should be targeted? Results of three pilots integrating a recent infection testing algorithm into routine programme activities in Kenya and Zimbabwe.

INTRODUCTION: Surveillance of recent HIV infections in national testing services has the potential to inform primary prevention programming activities. Focusing on procedures required to accurately determine recent infection, and the potential for recent infection surveillance to inform prevention efforts, we present the results of three independent but linked pilots of recency testing. METHODS: To distinguish recently acquired HIV infection from long-standing infection, in 2018 we applied a Recent Infection Testing Algorithm that combined a laboratory-based Limiting Antigen Avidity Enzyme Immunoassay with clinical information (viral-load; history of prior HIV diagnosis; antiretroviral therapy-exposure). We explored potential misclassification of test results and analysed the characteristics of participants with recent infection. We applied the algorithm in antenatal clinics providing prevention of mother-to-child transmission services in Siaya County, Kenya, outreach sites serving female sex workers in Zimbabwe, and routine HIV testing and counselling facilities in Nairobi, Kenya. In Nairobi, we also conducted recency testing among partners of HIV-positive participants. RESULTS: In Siaya County, 2.3% (10/426) of HIV-positive pregnant women were classified as recent. A risk factor analysis comparing women testing recent with those testing HIV-negative found women in their first trimester were significantly more likely to test recent than those in their second or third trimester. In Zimbabwe, 10.5% (33/313) of female sex workers testing HIV-positive through the outreach programme were classified recent. A risk factor analysis of women testing recent versus those testing HIV-negative, found no strong evidence of an association with recent infection. In Nairobi, among 532 HIV-positive women and men, 8.6% (46) were classified recent. Among partners of participants, almost a quarter of those who tested HIV-positive were classified as recent (23.8%; 5/21). In all three settings, the inclusion of clinical information helped improve the positive predictive value of recent infection testing by removing cases that were likely misclassified. CONCLUSIONS: We successfully identified recently acquired infections among persons testing HIV-positive in routine testing settings and highlight the importance of incorporating additional information to accurately classify recent infection. We identified a number of groups with a significantly higher proportion of recent infection, suggesting recent infection surveillance, when rolled-out nationally, may help in further targeting primary prevention efforts.