Impact of monovalent rotavirus vaccine on diarrhoea-associated post-neonatal infant mortality in rural communities in Malawi: a population-based birth cohort study

Background: Rotavirus is a major contributor to child mortality. The effect of rotavirus vaccine on diarrhoea mortality has been estimated in middle-income but not low-income settings, where mortality is high and vaccine effectiveness in reducing admissions to hospital is lower. Empirical population-based mortality studies have not been done in any setting. Malawi introduced monovalent rotavirus vaccine (RV1) in October, 2012. We aimed to investigate the impact and effectiveness of the RV1 vaccine in reducing diarrhoea-associated mortality in infants aged 10–51 weeks. Methods: In this population-based cohort study, we included infants born between Jan 1, 2012, and June 1, 2015, in Mchinji, Central Malawi and analysed data on those surviving 10 weeks. Individual vaccination status was extracted from caregiver-held records or report at home visits at 4 months and 1 year of age. Survival to 1 year was confirmed at home visit, or cause of death ascertained by verbal autopsy. We assessed impact (1 minus mortality rate ratio following vs before vaccine introduction) using Poisson regression. Among vaccine-eligible infants (born from Sept 17, 2012), we assessed effectiveness (1 minus hazard ratio) using Cox regression. Findings: Between Jan 1, 2012, and June 1, 2015, we recruited 48 672 livebirths in Mchinji, among whom 38 518 were vaccine-eligible and 37 570 survived to age 10 weeks. Two-dose versus zero-dose effectiveness analysis included 28 141 infants, of whom 101 had diarrhoea-associated death before 1 year of age. Diarrhoea-associated mortality declined by 31% (95% CI 1–52; p=0·04) after RV1 introduction. Effectiveness against diarrhoea-mortality was 34% (95% CI –28 to 66; p=0·22). Interpretation: RV1 was associated with substantial reduction in diarrhoea-associated deaths among infants in this rural sub-Saharan African setting. These data add considerable weight to evidence showing the impact of rotavirus vaccine programmes. Funding: Wellcome Trust and GlaxoSmithKline Biologicals. Before study commencement, extensive community engagement and consultation activities were undertaken with Traditional Authorities, village chiefs, health committees, women’s groups, district and environmental health officers, health-centre managers, and HSAs to ensure the study was welcome in communities and households. Malawi’s National Health Sciences Research Committee (#837) and the London School of Hygiene & Tropical Medicine (#6047) provided ethics approval. To assess population-level impact and individual-level effectiveness, we did a large scale, prospective, population-based birth cohort study. Site 1 (in Mchinji district) population was 456 516 persons in the 2008 national census, with a crude birth rate of 32 births per 1000 population and postneonatal infant mortality rate of 28 deaths per 1000 livebirths in 2015.15, 16 The district is rural and borders Zambia and Mozambique. Its sparsely populated villages and agricultural estates are interspersed with semiurban trading centres. The economy is based on subsistence maize farming. Electricity is available in 3·3% of households.16 This district was the location of a previous cluster randomised trial,17 with strong community support for research. It had the requisite infrastructure to expand to district-wide mortality surveillance and allowed us to do this type of study. We did a baseline district-wide census in March, 2012, to obtain household membership and create community-held household registers. To establish prospective household surveillance in 1832 census-enumerated villages within all 354 HSA clusters, we used a cadre of 1059 village-based key informants who were selected by village health committees. Key informants did continuous household surveillance and maintained updated paper-based household registers for about 100 households each, recording all pregnancies, birth outcomes, and deaths of children younger than 5 years, and of women of childbearing age. Key informants were supervised by and reported data monthly to 50 enumerators, who electronically scanned the updated registers. Enumerators did home visits to all liveborn infants at 4 and 12 months of age to record vaccination status and confirm survival. The system was supervised by eight monitoring and evaluation officers (MEOs). Deaths reported by informants were verified and specially trained MEOs determined cause of death by verbal autopsy captured electronically at the household, completed as culturally appropriate at least 2 weeks after death, by using the WHO 2012 verbal autopsy instrument (Open Data Kit software).18 We have published a detailed description of this surveillance system.14 Vaccine status was obtained from a scanned image of a vaccine record (health passport, which is held by the caregiver) issued by the government and caregiver report (completed during household visits by enumerators when infants were 4 and 12 months of age or by MEOs following death). Caregivers were asked directly about the receipt and date of each dose of every vaccine for which the child was age-eligible under the National Immunisation Programme. Vaccine status was cross checked against vaccination centre registers in a subset of records for quality assurance. Final vaccine status was determined per criteria outlined in the appendix. To compare reported versus recorded vaccine receipt, throughout recruitment mothers were interviewed by MEOs after infant vaccination at randomly allocated clinics. Additionally, throughout recruitment, enumerators collected sociodemographic data on maternal vitals, marital status, and educational level obtained, and data on house, water source, and sanitation quality. Quality controls were embedded in the database, which automatically triggered field checks in case of error or anomalous runs of data (eg, no births in a catchment for 3 months). MEOs met monthly to review data quality and timeliness and address field challenges. Infants surviving to at least 10 weeks of age who were born between Jan 1, 2012, and Sept 16, 2012, constituted the prevaccination cohort. Those born between Sept 17, 2012 (ie, eligible for first dose of RV1 on the date of vaccine introduction), and June 1, 2015, constituted the vaccine-age eligible cohort. Impact analysis compared both cohorts, whereas analysis of individual survival for effectiveness was done in the vaccine-eligible cohort only. Livebirths were followed up when the child had reached 1 year of age or death, or were excluded if they migrated. 1-year follow-up concluded on June 1, 2016. Diarrhoea-associated death was defined as any deceased child whose caregiver reported non-bloody diarrhoea in the illness preceding death upon direct closed questioning at verbal autopsy. We derived vaccine programme impact as 1 minus diarrhoea-associated mortality rate ratio in the vaccine-eligible cohort versus prevaccination cohort using Poisson regression adjusted for sociodemographic covariates (table 1). The relative brevity of the prevaccine introduction period at site 1 precluded adjustment by year. We also restricted analysis to between January and June, months with known high rotavirus prevalence in Blantyre, Malawi.19 To examine the association between population vaccine coverage and mortality, we did a Poisson regression of the mortality rate against two-dose vaccine coverage (proportion of two-dose-eligible infants in the population who actually received both doses) over time and by HSA cluster.17 For HSA cluster analysis of mortality versus vaccine coverage, we also adjusted for cluster-specific means of household level sociodemographic covariates, but we had no data on communal assets such as state of roads or public infrastructure. When plotting mortality rates over time, we used locally weighted moving average smoothing (appendix). Vaccine-eligible cohort description and multivariable Cox proportional hazards survival analysis, site 1 Data are n (%), unless otherwise specified. We calculated two-dose versus zero-dose effectiveness as 1 minus hazard ratio using Cox proportional hazards modelling of diarrhoea-associated death occurring at 10–51 completed weeks of life. Because children might die from causes other than diarrhoea, we also did competing risks–survival analysis. We used multivariable modelling to adjust for sociodemographic covariates using complete-case analysis (table 1). We have previously published20 the primary analysis plan and justification. In case of violation of the proportional hazards assumption and to better understand how effectiveness might be related to age, we did a fully parametric survival analysis using Royston-Parmar modelling.21 We examined whether cluster-level determinants influence individual level mortality hazard using random effects hierarchical models. In our sentinel hospital in Blantyre, rotavirus prevalence in severe gastroenteritis was 35% overall and 51% in peak periods; we therefore presumed rotavirus prevalence of 45% in diarrhoea-associated deaths.6, 22 Given that our published effectiveness against rotavirus gastroenteritis in Malawian infants in hospital was 64%, we assumed that effectiveness against very severe rotavirus gastroenteritis (leading to death) would be higher at 70–80%. Applying a presumed 76% reduction to the 45% of deaths presumed attributable to rotavirus, gave an effectiveness of 34% against all-cause diarrhoea-associated death. Based on our established surveillance before RV1 introduction, we expected 1500 births per month and a postneonatal infant mortality rate of 18 per 1000 livebirths, of which six were diarrhoea-associated. We assumed 60% mean vaccine coverage over the recruitment period. Inflating for 12% loss to follow-up, we required 36 293 infants who survived to 10 weeks to obtain 80% power to detect effectiveness of more than 34%. A demographic surveillance site (DSS) covering 35 000 individuals has operated in the remote lakeside region of Chilumba, northern Malawi since 2002.23 Crude birth rate was 30·8 per 1000 population in 2015, postneonatal infant mortality was 15 per 1000 livebirths, and electricity was available in 8·7% of households.16 This longstanding DSS provided robust data on historical mortality rates in infants before vaccine introduction from 2004 and was therefore considered useful for independent impact assessment. Individual survival analysis was precluded by the small total population. For this site, births, deaths, and migrations were reported monthly by village informants and validated in a rolling annual census (previously described).23 Verbal autopsies were done during home visits, as locally culturally appropriate, at least 2 weeks after death. Sociodemographic covariates and vaccine status were collected for age-eligible children at the time of census visit, with vaccination date transcribed from caregiver-held records (health passport) or caregiver reports. We used Poisson regression to test monthly diarrhoea-associated mortality rate among 10–51-week-old infants against vaccine coverage, adjusting for year to account for long-term trend.24 Unbeknown to us at planning phase, the Red Cross implemented rapid, widespread, and sustained water and sanitation interventions (WASH) across the DSS area alongside national vaccine introduction.25 Site 2 could therefore no longer serve its intended validation function, but afforded an unplanned opportunity to assess the combined impact of vaccination with WASH as a post-hoc analysis. Both study funders were provided the opportunity to review the study design. The funders had no role in data collection, analysis, or interpretation, or writing of the report. A preliminary version of this manuscript was reviewed by GlaxoSmithKline Biologicals for factual accuracy. All authors had full access to all study data. The authors are solely responsible for final content and interpretation, and share final responsibility for the decision to submit for publication.