Background: Confirmed local transmission of Zika Virus (ZIKV) in Texas and Florida have heightened the need for early and accurate indicators of self-sustaining transmission in high risk areas across the southern United States. Given ZIKV's low reporting rates and the geographic variability in suitable conditions, a cluster of reported cases may reflect diverse scenarios, ranging from independent introductions to a self-sustaining local epidemic. Methods: We present a quantitative framework for real-time ZIKV risk assessment that captures uncertainty in case reporting, importations, and vector-human transmission dynamics. Results: We assessed county-level risk throughout Texas, as of summer 2016, and found that importation risk was concentrated in large metropolitan regions, while sustained ZIKV transmission risk is concentrated in the southeastern counties including the Houston metropolitan region and the Texas-Mexico border (where the sole autochthonous cases have occurred in 2016). We found that counties most likely to detect cases are not necessarily the most likely to experience epidemics, and used our framework to identify triggers to signal the start of an epidemic based on a policymakers propensity for risk. Conclusions: This framework can inform the strategic timing and spatial allocation of public health resources to combat ZIKV throughout the US, and highlights the need to develop methods to obtain reliable estimates of key epidemiological parameters.

Background Ensuring equitable access to medical care with financial risk protection has been at the center of achieving universal health coverage. In this paper, we assess the levels and trends of inequalities in medical care utilization and household catastrophic health spending (HCHS) at the national and sub-national levels in Rwanda. Methods Using the Rwanda Integrated Living Conditions Surveys of 2005, 2010, 2014, and 2016, we applied multivariable logit models to generate the levels and trends of adjusted inequalities in medical care utilization and HCHS across the four survey years by four socio-demographic dimensions: poverty, gender, education, and residence. We measured the national- and district-level inequalities in both absolute and relative terms. Results At the national level, after controlling for other factors, we found significant inequalities in medical care utilization by poverty and education and -in HCHS by poverty in all four years. From 2005 to 2016, inequalities in medical care utilization by the four dimensions did not change significantly, while the inequality in HCHS by poverty was reduced significantly. At the district level, inequalities in both medical care utilization and HCHS were larger than zero in all four years and decreased over time. Conclusions Poverty and poor education were significant contributors to inequalities in medical care utilization and HCHS in Rwanda. Policies or interventions targeting poor households or households headed by persons receiving no education are needed in order to effectively reduce inequalities in medical care utilization and HCHS. Electronic supplementary material The online version of this article (10.1186/s12939-019-0953-y) contains supplementary material, which is available to authorized users.

Many developing countries have implemented social health insurance programs to protect their citizens against the financial risks of seeking healthcare. While many studies have explored how individual insurance enrollments affect catastrophic health spending (CHS) in the short term, there is a lack of evidence on the long-term macro-level effects of social health insurance on CHS in low- and middle-income countries. This study examines the long-term effects of Basic Medical Insurance (BMI) on individual CHS in China, a middle-income country that has witnessed one of the highest worldwide increases in CHS rates despite its remarkable achievement of universal health insurance coverage. Specifically, we used existing longitudinal data from 1989 to 2015, therein assessing BMI policy effects by constructing two macro-level indicators, including the year of BMI presence at the prefectural level and number of years relative to BMI introduction. We employed a three-level difference-in-differences approach for the estimation. There were two main findings. First, BMI policy did not significantly reduce the probability of incurring CHS for BMI enrollees over time. Years after BMI was introduced, the policy even predicted a significant increase in the probability of incurring CHS for individuals who shifted their enrollments from traditional insurance to BMI. Second, BMI policy had spillover effects on the increase in the probability of incurring CHS for non-BMI individuals a few years after its inception. We believe there are three possible explanations for these findings: (1) shrinking BMI service coverage compared to pre-existing government-funded insurance schemes, (2) a profit-driven hospital reform that induces the overuse of expensive medicines and diagnostic tests, and (3) the absence of strategic purchasing among local BMI agencies. We also discuss how relevant policy interventions may alleviate insurance-driven financial risks.

Subnational disparities in most health systems often defy ‘one-size-fits-all’ approach in policy implementation. When local authorities implement a national policy in a decentralized context, they behave as a strategic policy actor in specifying the central mandates, selecting appropriate tools, and setting key implementation parameters. Local policy discretion leads to diverse policy mixes across regions, thus complicating evidence-based evaluations of policy impacts. When measuring complex policy reforms, mainstream policy evaluation methodologies have tended to adopt simplified policy proxies that often disguise distinct policy choices across localities, leaving the heterogeneous effects of the same generic policy largely unknown. Using the emerging ‘text-as-data’ methodology and drawing from subnational policy documents, this study developed a novel approach to policy measurement through analysing policy big data. We applied this approach to examine the impacts of China’s Urban Employee Basic Medical Insurance (UEBMI) on individuals’ out-of-pocket spending. We found substantial disparities in policy choices across prefectures when categorizing the UEBMI policy framework into benefit-expansion and cost-containment reforms Overall, the UEBMI policies lowered enrollees’ out-of-pocket spending in prefectures that embraced both benefit-expansion and cost-containment reforms In contrast, the policies produced ill effects on out-of-pocket spending of UEBMI enrollees and uninsured workers in prefectures that carried out only benefit-expansion or cost-containment reforms The micro-level impacts of UEBMI enrolment on out-of-pocket spending were conditional on whether prefectural benefit-expansion and cost-containment reforms were undertaken in concert. Only in prefectures that promulgated both types of reforms did UEBMI enrolment reduce out-of-pocket spending. These findings contribute to a comprehensive text-mining measurement approach to locally diverse policy efforts and an integration of macro-level policy analysis and micro-level individual analysis. Contextualizing policy measurements would improve the methodological rigour of health policy evaluations. This paper concludes with implications for health policymakers in China and beyond.

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