Background 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. Results 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. Conclusion Despite lower-than expected survey uptake we believe our webRDS solution provides efficient and flexible means to survey a globally diverse population.

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 crisis and COVID-19 pandemic have affected mortality in Yemen. The security situation has limited access to affected populations and thus required novel alternatives 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 mortality estimation methods and survival analysis to calculate mortality and/or survivorship amongst respondents’ close family members in Yemen including adults aged 50+, siblings, and children under five years. 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 birth cohort and gender) 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 hazard of dying during the war/pandemic period; however, these results were non-significant. Sibling mortality amongst those aged 15–49 was 0.7 per 1000 person-years during the pre-war period compared to 1.1 during the war/pandemic period amongst males, and 0.8 versus 0.0 amongst females; however, these estimates reflected small numbers of deaths. The number of deaths amongst children under five in Yemen was too low to allow meaningful analysis; only three of the seven deaths in this group occurred during the analysis period. Conclusions Our data suggest increased mortality during the war/pandemic period, compared to the pre-war period, among elderly Yemenis. Our findings require careful interpretation 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; however, large numbers of respondents are likely required to achieve accurate mortality estimates and attempt adjustment for selection bias.

Background: 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 mortality in Yemen. We report here on the design of the webRDS solution and its implementation. We developed a webRDS solution comprised of an existing survey platform (i.e. ODK) and a bespoke RDS system. The RDS system was designed to administer and manage the survey cascade and included: 1) an application programming interface, 2) a study participant client, and 3) an administrator interface. Results: 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. Conclusion: Despite lower-than expected survey uptake we believe our webRDS solution provides efficient and flexible means to survey a globally diverse population.