Unmasking the truth: Experimental evidence of facemask compliance in Bangladesh, Kenya, and Nigeria during the COVID-19 pandemic.

High levels of compliance with public health measures are critical to ensure a successful response to the COVID-19 pandemic and other public health emergencies. However, most data on compliance are self-reported and the tendency to overreport due to social desirability could yield biased estimates of actual compliance. A list experiment is a widely used method to estimate social desirability bias in self-reported estimates of sensitive behaviours. We estimate rates of compliance with facemask mandates in Kenya, Nigeria, and Bangladesh using data from phone surveys conducted in March-April 2021. Data on compliance were collected from two different survey modules: a self-reported compliance module (stated) and a list experiment (elicited). We find large gaps between stated and elicited rates of facemask wearing for different groups depending on specific country contexts and high levels of overreporting of facemask compliance in self-reported surveys: there was an almost 40 percentage point gap in Kenya, 30 percentage points in Nigeria, and 20 percentage points in Bangladesh. We also observe differences in rates of self-reported facemask wearing among key groups but not using the elicited responses from the list experiment, which suggest that social desirability bias may vary by demographics. Data collected from self-reported surveys may not be reliable to monitor ongoing compliance with public health measures. Moreover, elicited compliance rates indicate levels of mask wearing are likely much lower than those estimated using self-reported data.

The impact of COVID-19 and national pandemic responses on health service utilisation in seven low- and middle-income countries.

BACKGROUND: The COVID-19 pandemic has disrupted health services worldwide, which may have led to increased mortality and secondary disease outbreaks. Disruptions vary by patient population, geographic area, and service. While many reasons have been put forward to explain disruptions, few studies have empirically investigated their causes. OBJECTIVE: We quantify disruptions to outpatient services, facility-based deliveries, and family planning in seven low- and middle-income countries during the COVID-19 pandemic and quantify relationships between disruptions and the intensity of national pandemic responses. METHODS: We leveraged routine data from 104 Partners In Health-supported facilities from January 2016 to December 2021. We first quantified COVID-19-related disruptions in each country by month using negative binomial time series models. We then modelled the relationship between disruptions and the intensity of national pandemic responses, as measured by the stringency index from the Oxford COVID-19 Government Response Tracker. RESULTS: For all the studied countries, we observed at least one month with a significant decline in outpatient visits during the COVID-19 pandemic. We also observed significant cumulative drops in outpatient visits across all months in Lesotho, Liberia, Malawi, Rwanda, and Sierra Leone. A significant cumulative decrease in facility-based deliveries was observed in Haiti, Lesotho, Mexico, and Sierra Leone. No country had significant cumulative drops in family planning visits. For a 10-unit increase in the average monthly stringency index, the proportion deviation in monthly facility outpatient visits compared to expected fell by 3.9% (95% CI: -5.1%, -1.6%). No relationship between stringency of pandemic responses and utilisation was observed for facility-based deliveries or family planning. CONCLUSIONS: Context-specific strategies show the ability of health systems to sustain essential health services during the pandemic. The link between pandemic responses and healthcare utilisation can inform purposeful strategies to ensure communities have access to care and provide lessons for promoting the utilisation of health services elsewhere.

The Unintended Consequences of Information Provision: The World Health Organization and Border Restrictions during COVID-19.

Why do some international agreements fail to achieve their goals? Rather than states' engaging in cheap talk, evasion, or shallow commitments, the World Health Organization's (WHO) International Health Regulations (IHR)-the agreement governing states' and WHO's response to global health emergencies-point to the unintended consequences of information provision. The IHR have a dual goal of providing public health protection from health threats while minimizing unnecessary interference in international traffic. As such, during major outbreaks WHO provides information about spread and severity, as well as guidance about how states should respond, primarily regarding border policies. During COVID-19, border restrictions such as entry restrictions, flight suspensions, and border closures have been commonplace even though WHO recommended against such policies when it declared the outbreak a public health emergency in January 2020. Building on findings from the 2014 Ebola outbreak, we argue that without raising the cost of disregarding (or the benefits of following) recommendations against border restrictions, information from WHO about outbreak spread and severity leads states to impose border restrictions inconsistent with WHO's guidance. Using new data from COVID-19, we show that WHO's public health emergency declaration and pandemic announcement are associated with increases in the number of states imposing border restrictions.

Resumen: ¿Por qué motivo algunos acuerdos internacionales no logran alcanzar sus objetivos? El Reglamento Sanitario Internacional (RSI) de la Organización Mundial de la Salud (OMS)­el acuerdo que rige la respuesta de los Estados y la OMS a las emergencias sanitarias mundiales­señala como motivo las consecuencias imprevistas del suministro de información, en lugar del discurso trivial, la evasión o los compromisos superficiales por parte de los Estados. El RSI tiene como doble objetivo proteger la salud pública de las amenazas sanitarias y minimizar las interferencias innecesarias en el tráfico internacional. Como tal, durante brotes importantes, la OMS proporciona información sobre la propagación y la gravedad, así como orientación sobre cómo deben responder los Estados, principalmente en lo que respecta a las políticas fronterizas. Sin embargo, durante la COVID-19, las restricciones fronterizas, tales como las restricciones de entrada, las suspensiones de vuelos y los cierres de fronteras, han sido habituales, a pesar de que la OMS recomendó no aplicar estas políticas cuando declaró el brote epidémico como emergencia de salud pública en enero de 2020. Basándonos en los resultados del brote de ébola de 2014, argumentamos que, sin aumentar el coste de ignorar (o los beneficios de seguir) las recomendaciones contra las restricciones fronterizas, la información de la OMS sobre la propagación y la gravedad del brote lleva a los Estados a imponer restricciones fronterizas que no son coherentes con las orientaciones de la OMS. Utilizando nuevos datos de la COVID-19, mostramos que la declaración de emergencia de salud pública de la OMS y el anuncio de pandemia están asociados con el aumento del número de estados que imponen restricciones fronterizas.

Résumé: Pourquoi certains accords internationaux n'atteignent-ils pas leurs objectifs? À l'inverse d'États se perdant dans des discussions superficielles, des pirouettes ou des engagements insignifiants, le Règlement sanitaire international (RSI) de l'Organisation mondiale de la santé (OMS), à savoir l'accord encadrant la réponse des États et de l'OMS aux situations d'urgence sanitaire internationales, évoque les conséquences imprévues de la transmission d'informations. Le RSI a un objectif double : protéger les populations contre les menaces pour la santé publique, tout en minimisant les interactions non nécessaires dans le trafic international. Par conséquent, lors des grandes épidémies, l'OMS fournit des informations relatives à la transmission et à la gravité des maladies, ainsi que des conseils quant aux mesures que les États doivent mettre en œuvre, principalement en ce qui concerne les politiques aux frontières. Pourtant, durant la pandémie de COVID-19, les restrictions aux frontières, telles que les limitations des entrées, les suspensions de vols et les fermetures, ont été monnaie courante, et ce bien que l'OMS ait déconseillé de telles pratiques lorsqu'elle a déclaré que l'épidémie constituait une urgence sanitaire, en janvier 2020. S'appuyant sur des travaux portant sur l'épidémie d'Ebola en 2014, nous soutenons, sans exagérer l'impact d'une non-conformité (ou les avantages d'une conformité) aux recommandations de l'OMS en matière de restrictions aux frontières, que les informations transmises par l'organisation en matière de transmission et de gravité de la maladie ont conduit les États à imposer des restrictions aux frontières non conformes auxdites recommandations. Grâce à de nouvelles données relatives au COVID-19, nous montrons que la déclaration d'urgence sanitaire et l'annonce de la pandémie par l'OMS se sont accompagnées d'une augmentation du nombre d'États imposant des restrictions aux frontières.

Reconceptualizing successful pandemic preparedness and response: A feminist perspective.

Pandemic preparedness and COVID-19 response indicators focus on public health outcomes (such as infections, case fatalities, and vaccination rates), health system capacity, and/or the effects of the pandemic on the economy, yet this avoids more political questions regarding how responses were mobilized. Pandemic preparedness country rankings have been called into question due to their inability to predict COVID-19 response and outcomes, and COVID-19 response indicators have ignored one of the most well documented secondary effects of the pandemic - its disproportionate effects on women. This paper analyzes pandemic preparedness and response indicators from a feminist perspective to understand how indicators might consider the secondary effects of the pandemic on women and other equity deserving groups. Following a discussion of the tensions that exist between feminist methodologies and the reliance on indicators by policymakers in preparing and responding to health emergencies, we assess the strengths and weakness of current pandemic preparedness and COVID-19 response indicators. The risk with existing pandemic preparedness and response indicators is that they give only limited attention to secondary effects of pandemics and inequities in terms of who is disproportionately affected. There is an urgent need to reconceptualize what 'successful' pandemic preparedness and response entails, moving beyond epidemiological and economic measurements. We suggest how efforts to design COVID response indicators on gender inclusion could inform pandemic preparedness and associated indicators.

Long-term spill-over impact of COVID-19 on health and healthcare of people with non-communicable diseases: a study protocol for a population-based cohort and health economic study.

INTRODUCTION: The COVID-19 pandemic has a significant spill-over effect on people with non-communicable diseases (NCDs) over the long term, beyond the direct effect of COVID-19 infection. Evaluating changes in health outcomes, health service use and costs can provide evidence to optimise care for people with NCDs during and after the pandemic, and to better prepare outbreak responses in the future. METHODS AND ANALYSIS: This is a population-based cohort study using electronic health records of the Hong Kong Hospital Authority (HA) CMS, economic modelling and serial cross-sectional surveys on health service use. This study includes people aged ≥18 years who have a documented diagnosis of diabetes mellitus, hypertension, cardiovascular disease, cancer, chronic respiratory disease or chronic kidney disease with at least one attendance at the HA hospital or clinic between 1 January 2010 and 31 December 2019, and without COVID-19 infection. Changes in all-cause mortality, disease-specific outcomes, and health services use rates and costs will be assessed between pre-COVID-19 and-post-COVID-19 pandemic or during each wave using an interrupted time series analysis. The long-term health economic impact of healthcare disruptions during the COVID-19 pandemic will be studied using microsimulation modelling. Multivariable Cox proportional hazards regression and Poisson/negative binomial regression will be used to evaluate the effect of different modes of supplementary care on health outcomes. ETHICS AND DISSEMINATION: The study was approved by the institutional review board of the University of Hong Kong, the HA Hong Kong West Cluster (reference number UW 21-297). The study findings will be disseminated through peer-reviewed publications and international conferences.

Understanding the Implementation of Antimicrobial Policies: Lessons from the Hong Kong Strategy and Action Plan.

In 2017, the Hong Kong Strategy and Action Plan on Antimicrobial Resistance 2017-2022 (HKSAP) was announced with the aim of tackling the growing threat of antimicrobial resistance (AMR) in Hong Kong. However, little is known about how the planned activities have been implemented. In this study, we examine the status of implementation of the HKSAP using the Smith Policy Implementation Process Model. Semi-structured interviews with 17 informants found that important achievements have been made, including launching educational and training activities targeting the public, farmers, and healthcare professionals; upgrading the AMR surveillance system; and strengthening AMR stewardship and infection control. Nevertheless, participants also identified barriers to greater implementation, such as tensions across sectors, ongoing inappropriate drug use and prescription habits, insufficient human and technical resources, as well as a weak accountability framework. Environmental factors such as the COVID-19 pandemic also affected the implementation of HKSAP. Our study indicated that expanding engagement with the public and professionals, creating a collaborative environment for policy implementation, and building a well-functioning monitoring and evaluation system should be areas to focus on in future AMR policies.

Understanding the societal factors of vaccine acceptance and hesitancy: evidence from Hong Kong.

OBJECTIVES: Vaccination is considered to be an important public health strategy for controlling the COVID-19 pandemic. Besides subjective evaluations of the vaccine and the health threat, societal factors have been seen as crucial to vaccination decisions. Based on a socioecological perspective, this study examines the role of societal factors in COVID-19 vaccine hesitancy in Hong Kong. STUDY DESIGN AND METHOD: An online survey was fielded between 25 and 28 June 2021, collecting 2753 complete responses. Multinomial logistic regression was conducted to examine how subjective evaluations of the vaccine (summarised by the 5C model - Confidence, Collective responsibility, Constraints, Complacency and Calculation), threat perception, interpersonal influences and institutional trust contribute to explaining three types of decision - acceptant (vaccinated, scheduled or indicated 'Yes'), hesitant (unvaccinated and indicated 'Maybe' on intention) and resistant (unvaccinated and indicated 'No'). RESULTS: A total of 43.2%, 21.7% and 35.1% of respondents were acceptant, hesitant and resistant. Although the 5C model remained useful in explaining vaccination decisions, respondents were heavily influenced by the decisions of their family, although they were less influenced by friends. Second, respondents tended to accept the vaccine when they had a weaker perception that the act is supportive of the government and were less resistant if they had stronger institutional trust. CONCLUSION: Under the low-incidence and low-trust environment such as Hong Kong, vaccination decisions are heavily influenced by family's decision and the perception of vaccination as socially and politically desirable. Our findings highlight the importance of a nuanced conception of interpersonal and political influence towards vaccine acceptance/hesitancy.

#WuhanDiary and #WuhanLockdown: gendered posting patterns and behaviours on Weibo during the COVID-19 pandemic.

Social media can be both a source of information and misinformation during health emergencies. During the COVID-19 pandemic, social media became a ubiquitous tool for people to communicate and represents a rich source of data researchers can use to analyse users' experiences, knowledge and sentiments. Research on social media posts during COVID-19 has identified, to date, the perpetuity of traditional gendered norms and experiences. Yet these studies are mostly based on Western social media platforms. Little is known about gendered experiences of lockdown communicated on non-Western social media platforms. Using data from Weibo, China's leading social media platform, we examine gendered user patterns and sentiment during the first wave of the pandemic between 1 January 2020 and 1 July 2020. We find that Weibo posts by self-identified women and men conformed with some gendered norms identified on other social media platforms during the COVID-19 pandemic (posting patterns and keyword usage) but not all (sentiment). This insight may be important for targeted public health messaging on social media during future health emergencies.

Food insecurity and COVID-19 risk in low- and middle-income countries.

The COVID-19 pandemic prompted social distancing, workplace closures, and restrictions on mobility and trade that had cascading effects on economic activity, food prices, and employment in low- and middle-income countries. Using longitudinal data from Bangladesh, Kenya, and Nigeria covering a period from October 2020 to April 2021, the paper assesses whether knowledge of a person infected with COVID-19 is associated with food insecurity, job loss and business closures, and coping strategies to smooth consumption. The likelihood of households to experience food insecurity at the extensive and intensive margins increased among those who knew an infected person in Bangladesh and Kenya.

Investigating Public Discourses Around Gender and COVID-19: a Social Media Analysis of Twitter Data.

We collected over 50 million tweets referencing COVID-19 to understand the public's gendered discourses and concerns during the pandemic. We filtered the tweets based on English language and among three gender categories: men, women, and sexual and gender minorities. We used a mixed-method approach that included topic modelling, sentiment analysis, and text mining extraction procedures including words' mapping, proximity plots, top hashtags and mentions, and most retweeted posts. Our findings show stark differences among the different genders. In relation to women, we found a salient discussion on the risks of domestic violence due to the lockdown especially towards women and girls, while emphasizing financial challenges. The public discourses around SGM mostly revolved around blood donation concerns, which is a reminder of the discrimination against some of these communities during the early days of the HIV/AIDS epidemic. Finally, the discourses around men were focused on the high death rates and the sentiment analysis results showed more negative tweets than among the other genders. The study concludes that Twitter influencers can drive major online discussions which can be useful in addressing communication needs during pandemics.

Using gender analysis matrixes to integrate a gender lens into infectious diseases outbreaks research.

Evidence shows that infectious disease outbreaks are not gender-neutral, meaning that women, men and gender minorities are differentially affected. This evidence affirms the need to better incorporate a gender lens into infectious disease outbreaks. Despite this evidence, there has been a historic neglect of gender-based analysis in health, including during health crises. Recognizing the lack of available evidence on gender and pandemics in early 2020 the Gender and COVID-19 project set out to use a gender analysis matrix to conduct rapid, real-time analyses while the pandemic was unfolding to examine the gendered effects of the coronavirus disease 2019 pandemic. This paper reports on what a gender analysis matrix is, how it can be used to systematically conduct a gender analysis, how it was implemented within the study, ways in which the findings from the matrix were applied and built upon, and challenges encountered when using the matrix methodology.

Addressing missing values in routine health information system data: an evaluation of imputation methods using data from the Democratic Republic of the Congo during the COVID-19 pandemic.

BACKGROUND: Poor data quality is limiting the use of data sourced from routine health information systems (RHIS), especially in low- and middle-income countries. An important component of this data quality issue comes from missing values, where health facilities, for a variety of reasons, fail to report to the central system. METHODS: Using data from the health management information system in the Democratic Republic of the Congo and the advent of COVID-19 pandemic as an illustrative case study, we implemented seven commonly used imputation methods and evaluated their performance in terms of minimizing bias in imputed values and parameter estimates generated through subsequent analytical techniques, namely segmented regression, which is widely used in interrupted time series studies, and pre-post-comparisons through paired Wilcoxon rank-sum tests. We also examined the performance of these imputation methods under different missing mechanisms and tested their stability to changes in the data. RESULTS: For regression analyses, there were no substantial differences found in the coefficient estimates generated from all methods except mean imputation and exclusion and interpolation when the data contained less than 20% missing values. However, as the missing proportion grew, k-NN started to produce biased estimates. Machine learning algorithms, i.e. missForest and k-NN, were also found to lack robustness to small changes in the data or consecutive missingness. On the other hand, multiple imputation methods generated the overall most unbiased estimates and were the most robust to all changes in data. They also produced smaller standard errors than single imputations. For pre-post-comparisons, all methods produced p values less than 0.01, regardless of the amount of missingness introduced, suggesting low sensitivity of Wilcoxon rank-sum tests to the imputation method used. CONCLUSIONS: We recommend the use of multiple imputation in addressing missing values in RHIS datasets and appropriate handling of data structure to minimize imputation standard errors. In cases where necessary computing resources are unavailable for multiple imputation, one may consider seasonal decomposition as the next best method. Mean imputation and exclusion and interpolation, however, always produced biased and misleading results in the subsequent analyses, and thus, their use in the handling of missing values should be discouraged.

Strengthening national capacities for pandemic preparedness: a cross-country analysis of COVID-19 cases and deaths.

The International Health Regulations-State Party Annual Reporting (IHR-SPAR) index and the Global Health Security Index (GHSI) have been developed to aid in strengthening national capacities for pandemic preparedness. We examined the relationship between country-level rankings on these two indices, along with two additional indices (the Universal Health Coverage Service Coverage Index and World Bank Worldwide Governance Indicator (n = 195)) and compared them to the country-level reported coronavirus disease (COVID-19) cases and deaths (Johns Hopkins University COVID-19 Dashboard) through 17 June 2020. Ordinary least squares regression models were used to compare weekly reported COVID-19 cases and death rates per million in the first 12 weeks of the pandemic between countries classified as low, middle and high ranking on each index while controlling for country socio-demographic information. Countries with higher GHSI and IHR-SPAR index scores experienced fewer reported COVID-19 cases and deaths but only for the first 8 weeks after the country's first case. For the GHSI, this association was further limited to countries with populations below 69.4 million. For both the GHSI and IHR-SPAR, countries with a higher sub-index score in human resources for pandemic preparedness reported fewer COVID-19 cases and deaths in the first 8 weeks after the country's first reported case. The Universal Health Coverage Service Coverage Index and Worldwide Governance Indicator country-level rankings were not associated with COVID-19 outcomes. The associations between GHSI and IHR-SPAR scores and COVID-19 outcomes observed in this study demonstrate that these two indices, although imperfect, may have value, especially in countries with a population under 69.4 million people for the GHSI. Preparedness indices may have value; however, they should continue to be evaluated as policy makers seek to better prepare for future global public health crises.

A tale of two city-states: A comparison of the state-led vs civil society-led responses to COVID-19 in Singapore and Hong Kong.

The East Asian experience in tackling COVID-19 has been highly praised, but this high-level generalisation neglects variation in pandemic response measures adopted across countries as well as the socio-political factors that shaped them. This paper compares the early pandemic response in Singapore and Hong Kong, two Asian city-states of similar sizes, a shared history of SARS, and advanced medical systems. Although both were able to contain the virus, they did so using two very different approaches. Drawing upon data from a cross-national, probability sample Internet survey conducted in May 2020 as well as media and mobility data, we argue that the different approaches were the result of the relative strength of civil society vs. the state at the outset of the outbreak. In protest-ridden Hong Kong, low governmental trust bolstered civil society, which focused on self-mobilisation and community mutual-help. In Singapore, a state-led response model that marginalised civil society brought early success but failed to stem an outbreak among its segregated migrant population. Our findings show that an active civil society is pivotal to effective outbreak response and that trust in government may not have been as important as a factor in these contexts.

The failure of private health services: COVID-19 induced crises in low- and middle-income country (LMIC) health systems.

For decades, governments and development partners promoted neoliberal policies in the health sector in many LMICs, largely motivated by the belief that governments in these countries were too weak to provide all the health services necessary to meet population needs. Private health markets became the governance and policy solution to improve the delivery of health services which allowed embedded forms of market failure to persist in these countries and which were exposed during the COVID-19 pandemic. In this article, we analyse the manifestations of these market failures using data from an assembled database of COVID-19 related news items sourced from the Global Database of Events, Language, and Tone. Specifically, we identify how pre-existing market failure and failures of redistribution have led to the rise of three urgent crises in LMICs: a financial and liquidity crisis among private providers, a crisis of service provision and pricing, and an attendant crisis in state-provider relations. The COVID-19 pandemic has therfore exposed important failures of the public-private models of health systems and provides an opportunity to rethink the future orientation of national health systems and commitments towards Universal Health Coverage.

Impact of the COVID-19 pandemic and response on the utilisation of health services in public facilities during the first wave in Kinshasa, the Democratic Republic of the Congo.

INTRODUCTION: Health service use among the public can decline during outbreaks and had been predicted among low and middle-income countries during the COVID-19 pandemic. In March 2020, the government of the Democratic Republic of the Congo (DRC) started implementing public health measures across Kinshasa, including strict lockdown measures in the Gombe health zone. METHODS: Using monthly time series data from the DRC Health Management Information System (January 2018 to December 2020) and interrupted time series with mixed effects segmented Poisson regression models, we evaluated the impact of the pandemic on the use of essential health services (outpatient visits, maternal health, vaccinations, visits for common infectious diseases and non-communicable diseases) during the first wave of the pandemic in Kinshasa. Analyses were stratified by age, sex, health facility and lockdown policy (ie, Gombe vs other health zones). RESULTS: Health service use dropped rapidly following the start of the pandemic and ranged from 16% for visits for hypertension to 39% for visits for diabetes. However, reductions were highly concentrated in Gombe (81% decline in outpatient visits) relative to other health zones. When the lockdown was lifted, total visits and visits for infectious diseases and non-communicable diseases increased approximately twofold. Hospitals were more affected than health centres. Overall, the use of maternal health services and vaccinations was not significantly affected. CONCLUSION: The COVID-19 pandemic resulted in important reductions in health service utilisation in Kinshasa, particularly Gombe. Lifting of lockdown led to a rebound in the level of health service use but it remained lower than prepandemic levels.

A thematic analysis of Instagram's gendered memes on COVID-19.

We investigate the gendered use of Instagram memes on COVID-19 using a mixed-analysis approach. We find that memes referencing women are mostly related to community support and healthcare, which often express gratitude for frontline workers, while the majority of memes on men refer to news and promotion as well as suffering due to the high death rates and other financial hardships. As for sexual and gender minorities, memes mostly mention community support similar to the case of the memes referencing women. We argue that internet memes offer insight into ongoing trends in the public's perceptions of pandemics, and they should be further examined because they often communicate vital information on gender groups and public health.

Managing borders during public health emergencies of international concern: a proposed typology of cross-border health measures.

BACKGROUND: The near universal adoption of cross-border health measures during the COVID-19 pandemic worldwide has prompted significant debate about their effectiveness and compliance with international law. The number of measures used, and the range of measures applied, have far exceeded previous public health emergencies of international concern. However, efforts to advance research, policy and practice to support their effective use has been hindered by a lack of clear and consistent definition. RESULTS: Based on a review of existing datasets for cross-border health measures, such as the Oxford Coronavirus Government Response Tracker and World Health Organization Public Health and Social Measures, along with analysis of secondary and grey literature, we propose six categories to define measures more clearly and consistently - policy goal, type of movement (travel and trade), adopted by public or private sector, level of jurisdiction applied, stage of journey, and degree of restrictiveness. These categories are then brought together into a proposed typology that can support research with generalizable findings and comparative analyses across jurisdictions. Addressing the current gaps in evidence about travel measures, including how different jurisdictions apply such measures with varying effects, in turn, enhances the potential for evidence-informed decision-making based on fuller understanding of policy trade-offs and externalities. Finally, through the adoption of standardized terminology and creation of an agreed evidentiary base recognized across jurisdictions, the typology can support efforts to strengthen coordinated global responses to outbreaks and inform future efforts to revise the WHO International Health Regulations (2005). CONCLUSIONS: The widespread use of cross-border health measures during the COVID-19 pandemic has prompted significant reflection on available evidence, previous practice and existing legal frameworks. The typology put forth in this paper aims to provide a starting point for strengthening research, policy and practice.