Social Interactions and Malaria Preventive Behaviors in Sub-Saharan Africa

描述（由申请人提供）：疟疾仍然是世界范围内的一个主要健康问题。根据世界卫生组织2008年的数据，约有85万人死于疟疾，其中89%以上发生在非洲。可悲的是，现有的技术可以预防、诊断甚至治愈疟疾。在临床试验中显示有效的预防性技术包括使用驱虫蚊帐、孕期间歇预防治疗以及使用青蒿素联合疗法迅速有效地治疗疟疾。尽管撒哈拉以南非洲的大多数人都知道这些技术的存在，但仍有大量个人不采用这些技术。itn、IPT和ACT是相对较新的技术，它们的益处可能对一般人群并不明显，因为个人需要不断地体验这些技术以确定其有效性。当面临不确定性下的选择时，个体有动机从邻居的行为和结果中学习。邻居的行为也可能产生同伴压力，促使他们做出某些行为。本研究的目的是利用1999年至2010年间34个撒哈拉以南国家的所有人口健康调查（DHS）、疟疾指标调查（MIS）和多指标类集调查（MICS）的数据，确定这些社会互动对ITNs、IPT和ACT的采用和传播的重要性。对于每个国家，我们都有多个关于蚊帐和驱虫蚊帐的所有权和使用情况、IPT使用情况和acts使用情况的信息波。社会互动产生了社会溢出效应，即政府政策鼓励某些个人采用这些技术的效果，也会通过这些个人对其邻居行为的影响产生间接影响。如果社会互动是重要的，那么疟疾预防行为决定因素的微小变化可能导致总体水平上的高度变化。众所周知，从其他现象（在同伴中产生类似结果）中识别社会互动的问题是巨大的。本研究通过比较外生变量在个人和群体层面上对疟疾预防行为的影响来计算社会溢出的大小，并将群体定义为一个国家的一个地区或地区。在存在社会溢出效应的情况下，这两种效应的比值将显著大于1，这意味着一项能够说服一小部分有影响力的人采用该技术的社会政策可能会在社区层面产生很大的影响。

DESCRIPTION (provided by applicant): Malaria remains a major health problem worldwide. According to the World Health Organization in 2008 there were approximately 850,000 deaths related to malaria, with over 89% occurring in Africa. The tragedy is that technologies exist that can prevent, diagnose and even cure malaria. Preventative technologies that have been shown to be effective in clinical trials include the use of insecticide-treated mosquito nets (ITNs), intermittent preventive treatment during pregnancy (IPT) and prompt and effective treatment of malaria using artemisinin combination therapy (ACT). Despite the fact that most people in Sub-Saharan Africa are aware of the existence of these technologies, a large number of individuals do not adopt them. ITNs, IPT, and ACT are relatively new and their benefits may not be widely evident to the general population because individuals need to continuously experience these technologies to ascertain their effectiveness. When facing choices under uncertainty, individuals have incentives to learn from the actions and outcomes of their neighbors. The action of neighbors may also create peer pressure to engage in certain behaviors. The objective of this study is to determine the importance of these social interactions in the adoption and spread of ITNs, IPT, and ACT using data from all the Demographic Health Surveys (DHS), Malaria Indicator Surveys (MIS), and Multiple Indicator Cluster Surveys (MICS) between 1999 and 2010 for 34 Sub- Saharan countries. For each country we have multiple waves with information on ownership and usage of mosquito nets and ITN, usage of IPT and usage of ACT. Social interactions create a social spillover, where the effect of a government policy that encourages some individuals to adopt these technologies will also have an indirect effect through the influence of these individuals on the behavior of their neighbors. If social interactions are important, small changes in the determinants of malaria-preventative behaviors may lead to a high variation at the aggregate level. It is well known that the problems of identifying social interactions from other phenomena (that give rise to similar outcomes among peers) are immense. This study calculates the size of the social spillover by comparing the effects of an exogenous variable on the malaria preventive behavior at both the individual and group level, defining a group as a region or district of a country. In the presence of social spillovers, the ratio of these two effects will be significantly greater than one, implying that a social policy that convinces a small group of influential people to adopt the technology could have large effects at the community level. PUBLIC HEALTH RELEVANCE: Several technologies have been identified as being highly effective in preventing malaria and although most individuals in Sub-Saharan Africa are aware that these technologies exist, studies have shown that people do not fully use them. This project will study the importance of social interactions such as learning from or being influenced by others on the adoption of some of these technologies (for example usage of insecticide-treated mosquito nets (ITNs)). Social interactions will create social spillovers, where the effect of a government policy that encourages some individuals to adopt these technologies will also have a multiplying effect at the aggregate level through the influence of these individuals on the behavior of their neighbors, who will then also influence additional neighbors and so on.