Tracking health seeking behavior during an Ebola outbreak via mobile phones and SMS
Tracking health seeking behavior during an Ebola outbreak via mobile phones and SMS
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DOI：
10.1038/s41746-018-0055-z
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发表时间：
2018-10-02
影响因子：
15.2
通讯作者：
Chunara, Rumi
中科院分区：
文献类型：
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作者：
Feng, Shuo;Grepin, Karen A.;Chunara, Rumi
最近在西非爆发的埃博拉疫情是一个范例，说明有必要迅速衡量人口层面的求医行为，以便了解紧急情况下的医疗保健利用情况。利用移动电话的高普及率，我们在利比里亚开展了一项全国性短信民意调查，并收集了2015年3月至6月期间6694人在疫情期间的个人健康和就医行为数据。我们使用倾向得分匹配来生成平衡的子样本，将我们的调查结果与最近一次家庭调查（2013年利比里亚人口健康调查）的结果进行了比较。我们发现匹配的亚组总体上具有相似的分娩l(o)阳性模式，并且利用出生日期的数据，我们能够显示，与疫情爆发后相比，在医院分娩的人数显著减少（p < 0.05），这与使用基于医疗保健的数据进行的回顾性研究的结果一致。通过短信直接评估个人的行为还可以分别衡量公共和私营部门的设施利用情况，这在包括利比里亚在内的主要依赖政府数据来源的国家的其他研究中一直是一个挑战。通过这样做，我们的数据表明，在疫情爆发后，基于公共设施的交付量恢复到基线值。因此，我们证明，通过适当的方法方法来考虑不同的人口分母，通过手机工具（如短信投票）获取的数据可以作为现有数据收集策略的重要低成本补充，特别是在比通过调查获得的更高频数据有用的情况下。
The recent Ebola outbreak in West Africa was an exemplar for the need to rapidly measure population-level health-seeking behaviors, in order to understand healthcare utilization during emergency situations. Taking advantage of the high prevalence of mobile phones, we deployed a national SMS-poll and collected data about individual-level health and health-seeking behavior throughout the outbreak from 6694 individuals from March to June 2015 in Liberia. Using propensity score matching to generate balanced subsamples, we compared outcomes in our survey to those from a recent household survey (the 2013 Liberian Demographic Health Survey). We found that the matched subgroups had similar patterns of delivery l(o)cation in aggregate, and utilizing data on the date of birth, we were able to show that facility-based deliveries were significantly decreased during, compared to after the outbreak (p < 0.05) consistent with findings from retrospective studies using healthcare-based data. Directly assessing behaviors from individuals via SMS also enabled the measurement of public and private sector facility utilization separately, which has been a challenge in other studies in countries including Liberia which rely mainly on government sources of data. In doing so, our data suggest that public facility-based deliveries returned to baseline values after the outbreak. Thus, we demonstrate that with the appropriate methodological approach to account for different population denominators, data sourced via mobile tools such as SMS polling could serve as an important low-cost complement to existing data collection strategies especially in situations where higher-frequency data than can be feasibly obtained through surveys is useful.