World Medical & Health Policy最新文献

In March 2020, the outbreak of COVID-19 was officially declared a global pandemic by the World Health Organization. Given the novelty of the virus, and hence, lack of official guidance on effective containment strategies, individual countries opted for different containment approaches ranging from herd immunity to strict lockdown. The opposing strategies followed by the United Kingdom and its former colony, Malaysia, stand exemplary for this. Real-time polymerase chain reaction was implemented for testing in both counties. Malaysia acted with strict quarantining rules and infection surveillance. The United Kingdom followed an initially lenient, herd-immunity approach with strict lockdown only enforced weeks later. Although based on the same health-care structure historically, Malaysia developed a more unified health system compared with the United Kingdom. We suggest that this more centralized structure could be one possible explanation for why Malaysia was able to react in a more timely and efficient manner, despite its closer geographic proximity to China. We further explore how the differences in testing and quarantining strategy, as well as political situation and societal compliance could account for the discrepancy in the United Kingdom's versus Malaysia's relative success of COVID-19 containment.

The COVID-19 pandemic has not spared the Middle East and North Africa (MENA) Region. MENA is one of the most politically, socially, and economically heterogeneous regions in the world, a characteristic reflected in its governments' responses to COVID-19. About two-thirds of these governments issued coronavirus-related stay-at-home orders (SAHOs), one of the most effective tools public health officials have for slowing the spread of infectious diseases. While SAHOs are very effective in terms of countering infectious diseases, they are extremely disruptive in nonhealth domains. The objective of this study is to identify reliable factors related to health care policy making that shaped the decisions of MENA governments to issue a SAHO or not in response to COVID-19. The results identify specific political, social, and medical factors that played important roles and provide a look at early government responses to a global health crisis in a heterogeneous region of the world.

Genetic testing plays an increasingly important role in the diagnosis and potential treatment of inherited and rare conditions, such as aniridia-a disease that leads to abnormal eye development, as well as in health research on these conditions. As genetic testing is increasingly sought for accurate and early diagnosis of rare genetic disorders and in the context of direct-to-consumer genomics, it is critical to examine the public-facing information about access to these services and reimbursement policies. We conducted a targeted policy and public-facing resource search. Our analysis of resources available for the patient community revealed that there is very little practical guidance available about access and reimbursement for genetic testing for rare diseases. Greater clarity in public-facing resources about genetic testing would be beneficial to the patient community as it would promote informed choices about the procedure, mitigate potential harms associated with lack of information and enable patient engagement in their own health care.

This study was performed to analyze the accuracy of health-related information on Twitter during the coronavirus disease 2019 (COVID-19) pandemic. Authors queried Twitter on three dates for information regarding COVID-19 and five terms (cure, emergency or emergency room, prevent or prevention, treat or treatments, vitamins or supplements) assessing the first 25 results with health-related information. Tweets were authoritative if written by governments, hospitals, or physicians. Two physicians assessed each tweet for accuracy. Metrics were compared between accurate and inaccurate tweets using χ ² analysis and Mann-Whitney U. A total of 25.4% of tweets were inaccurate. Accurate tweets were more likely written by Twitter authenticated authors (49.8% vs. 20.9%, 28.9% difference, 95% confidence interval [CI]: 17.7-38.2) with accurate tweet authors having more followers (19,491 vs. 7346; 3446 difference, 95% CI: 234-14,054) versus inaccurate tweet authors. Likes, retweets, tweet length, botometer scores, writing grade level, and rank order did not differ between accurate and inaccurate tweets. We found 1/4 of health-related COVID-19 tweets inaccurate indicating that the public should not rely on COVID-19 health information written on Twitter. Ideally, improved government regulatory authority, public/private industry oversight, independent fact-checking, and artificial intelligence algorithms are needed to ensure inaccurate information on Twitter is removed.