BACKGROUND: The ongoing war in Yemen has created a severe and protracted crisis that has left nearly three-quarters of the population in need of urgent humanitarian assistance. Despite eight years of conflict there exist few robust estimates of how the conflict (and the conflict combined with the COVID-19 pandemic) have affected mortality in Yemen. As the security situation has limited access to affected populations we have designed a novel alternative to local mortality surveys.
METHODS: We used a web-based, respondent-driven sampling method to disseminate a mortality survey amongst the global Yemeni diaspora. We used Cox proportional hazards survival models to estimate the association between the exposure (i.e. between the pre-conflict, conflict, and conflict/pandemic periods) and mortality risk, adjusted for gender and birth cohort.
RESULTS: Eighty-nine eligible respondents completed the survey. Respondents provided data on the status of 1704 individuals of whom 85 (5%) had died; of these 65 (3.8%) were reported to have died in Yemen. An analysis of survivorship of respondents\' parents after their 50th birthday (adjusted for gender and birth cohort) provided weak evidence that the war and pandemic periods were associated with higher mortality when compared to the pre-war period. Analysis of the subset of individuals who died in Yemen also suggested an increased, but non-significant hazard of dying during the war/pandemic period: this association tended towards significance when allowing for varying degrees of out-migration from Yemen across the cohort. The number of deaths amongst respondents\' siblings and children under five in Yemen were too low to allow meaningful analysis.
CONCLUSIONS: Our data suggest increased mortality during the war/pandemic period, compared to the pre-war period, among older Yemeni adults. However, our findings require careful interpretation as our study design cannot establish causation, and as our small and non-representative sample appeared skewed towards higher-income, urban communities. Surveys of diaspora populations offer a promising means of describing mortality patterns in crisis-affected populations; though, large numbers of respondents are likely required to achieve accurate mortality estimates and to adjust for selection bias.

Respondent-driven sampling (RDS) refers both to a chain-referral sampling method and an analytical model for analysing sampled data. Web-based respondent-driven sampling (webRDS) uses internet-based recruitment coupled with an electronic survey to carry out RDS studies; there is currently no commercially available webRDS solution. We designed and developed a webRDS solution to support a research study aimed at estimating conflict-attributable mortality in Yemen. Our webRDS solution is composed of an existing survey platform (i.e. ODK) and a bespoke RDS system. The RDS system is designed to administer and manage an RDS survey cascade and includes: (1) an application programming interface, (2) a study participant client, and (3) an administrator interface. We report here on the design of the webRDS solution and its implementation.
We consulted members of the Yemeni diaspora throughout the development of the solution. Technical obstacles were largely the result of: WhatsApp\'s policies on bulk messaging and automated messaging behaviour, the inherent constraints of SMS messaging, and SMS filtering behaviour. Language support was straight-forward yet time consuming. Survey uptake was lower than expected. Factors which may have impacted uptake include: our use of consumable survey links, low interest amongst the diaspora population, lack of material incentives, and the length and subject matter of the survey itself. The SMS/WhatsApp messaging integration was relatively complex and limited the information we could send potential participants.
Despite lower-than expected survey uptake we believe our webRDS solution provides efficient and flexible means to survey a globally diverse population.

Sibling survival histories are a major source of adult mortality estimates in countries with incomplete death registration. We evaluate age and date reporting errors in sibling histories collected during a validation study in the Niakhar Health and Demographic Surveillance System (Senegal). Participants were randomly assigned to either the Demographic and Health Survey questionnaire or a questionnaire incorporating an event history calendar, recall cues, and increased probing strategies. We linked 60-62 per cent of survey reports of siblings to the reference database using manual and probabilistic approaches. Both questionnaires showed high sensitivity (>96 per cent) and specificity (>97 per cent) in recording siblings\' vital status. Respondents underestimated the age of living siblings, and age at and time since death of deceased siblings. These reporting errors introduced downward biases in mortality estimates. The revised questionnaire improved reporting of age of living siblings but not of age at or timing of deaths.

BACKGROUND: An adequate forecasting model of mortality that allows an analysis of different population changes is a topic of interest for countries in demographic transition. Phenomena such as the reduction of mortality, ageing, and the increase in life expectancy are extremely useful in the planning of public policies that seek to promote the economic and social development of countries. To our knowledge, this paper is one of the first to evaluate the performance of mortality forecasting models applied to abridged life tables.
OBJECTIVE: Select a mortality model that best describes and forecasts the characteristics of mortality in Colombia when only abridged life tables are available.
METHODS: We used Colombian abridged life tables for the period 1973-2005 with data from the Latin American Human Mortality Database. Different mortality models to deal with modeling and forecasting probability of death are presented in this study. For the comparison of mortality models, two criteria were analyzed: graphical residuals analysis and the hold-out method to evaluate the predictive performance of the models, applying different goodness of fit measures.
RESULTS: Only three models did not have convergence problems: Lee-Carter (LC), Lee-Carter with two terms (LC2), and Age-Period-Cohort (APC) models. All models fit better for women, the improvement of LC2 on LC is mostly for central ages for men, and the APC model\'s fit is worse than the other two. The analysis of the standardized deviance residuals allows us to deduce that the models that reasonably fit the Colombian mortality data are LC and LC2. The major residuals correspond to children\'s ages and later ages for both sexes.
CONCLUSIONS: The LC and LC2 models present better goodness of fit, identifying the principal characteristics of mortality for Colombia.Mortality forecasting from abridged life tables by sex has clear added value for studying differences between developing countries and convergence/divergence of demographic changes.

This paper provides an overview of trends in mortality in children aged under 5 and adults between the ages of 15 and 60 in sub-Saharan Africa, using data on the survival of the children and siblings collected in Demographic and Health Surveys. If conspicuous stalls in the 1990s are disregarded, child mortality levels have generally declined and converged over the last 30-40 years. In contrast, adult mortality in many East and Southern African countries has increased markedly, echoing earlier increases in the incidence of HIV. In recent years, adult mortality levels have begun to decline once again in East Africa, in some instances before the large-scale expansion of antiretroviral therapy programmes. More surprising is the lack of sustained improvements in adult survival in some countries that have not experienced severe HIV epidemics. Because trends in child and adult mortality do not always evolve in tandem, we argue that model-based estimates, inferred by matching indices of child survival onto standard mortality schedules, can be very misleading.