National and sub-national variation in patterns of febrile case management in sub-Saharan Africa.
National and sub-national variation in patterns of febrile case management in sub-Saharan Africa.
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DOI：
10.1038/s41467-018-07536-9
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发表时间：
2018-11-26
影响因子：
16.6
通讯作者：
Tatem AJ
中科院分区：
文献类型：
--
作者：
Alegana VA;Maina J;Ouma PO;Macharia PM;Wright J;Atkinson PM;Okiro EA;Snow RW;Tatem AJ
鉴于国家医疗保健覆盖范围的差距，了解发烧的寻求治疗行为对于管理儿童疾病和减少死亡至关重要。在这里，我们利用撒哈拉以南非洲 29 个国家的地理参考公共卫生设施数据库（n = 86,442 个设施）对五岁以下儿童发烧的家庭调查数据进行三角测量，以估计在公共设施寻求发烧治疗的概率。贝叶斯项目反应理论框架用于根据报告的发烧发作、治疗选择、居住地以及前往最近的公共部门卫生机构的估计旅行时间来估计这种概率。调查结果显示国家间和国家内部存在差异，在 16 个国家中寻求发烧治疗的可能性低于 50%。结果凸显了投资公共医疗保健和相关数据库的必要性。公共部门使用的变化表明需要将此类模型纳入未来的传染病负担估计中。寻求发烧治疗被广泛用于估计儿童感染的治疗情况，但跨国比较是有问题的。在这里，作者通过量化个人层面的潜在变量，估计了在 29 个国家的公共设施寻求发烧治疗的概率。
Given national healthcare coverage gaps, understanding treatment-seeking behaviour for fever is crucial for the management of childhood illness and to reduce deaths. Here, we conduct a modelling study triangulating household survey data for fever in children under the age of five years with georeferenced public health facility databases (n = 86,442 facilities) in 29 countries across sub-Saharan Africa, to estimate the probability of seeking treatment for fever at public facilities. A Bayesian item response theory framework is used to estimate this probability based on reported fever episodes, treatment choice, residence, and estimated travel-time to the nearest public-sector health facility. Findings show inter- and intra-country variation, with the likelihood of seeking treatment for fever less than 50% in 16 countries. Results highlight the need to invest in public healthcare and related databases. The variation in public sector use illustrates the need to include such modelling in future infectious disease burden estimation. Treatment-seeking for fever is widely used to estimate treatment of childhood infections, but cross-country comparisons are problematic. Here, the authors estimate the probability of seeking treatment for fever at public facilities across 29 countries by quantifying person-level latent variables.
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影响因子：
15.8
作者：
Bejon P;Berkley JA;Mwangi T;Ogada E;Mwangi I;Maitland K;Williams T;Scott JA;English M;Lowe BS;Peshu N;Newton CR;Marsh K
通讯作者：
Marsh K
影响因子：
2.8
作者：
McLaren ZM;Ardington C;Leibbrandt M
通讯作者：
Leibbrandt M
影响因子：
3
作者：
Dixit, Amruta;Lee, Ming-Chieh;Yan, Guiyun
通讯作者：
Yan, Guiyun
影响因子：
158.5
作者：
D'Acremont, Valerie;Kilowoko, Mary;Genton, Blaise
通讯作者：
Genton, Blaise
影响因子：
2.4
作者：
Fox, J. -P.;Wyrick, Cheryl
通讯作者：
Wyrick, Cheryl