Health Policy Responses Research Articles

Exploring Prehospital Data for Pandemic Preparedness: A Western Brazilian Amazon Case Study on COVID-19.

The timely management of rapidly evolving epidemiological scenarios caused by disease outbreaks is crucial to prevent devastating consequences. However, delayed laboratory diagnostics can hamper swift health policy and epidemic response, especially in remote regions such as the western Brazilian Amazon. The aim of the article is to analyze the impact of the COVID-19 pandemic on the volume and characteristics of emergency medical services (EMS) in Manaus, focusing on how the pandemic affected sensitive indicators such as response time and the use of advanced life support ambulances. Additionally, the study seeks to understand how changes in prehospital EMS patterns, triggered by the pandemic, could be utilized as health surveillance tools, enabling a more rapid response in epidemic scenarios. This retrospective, descriptive study included data from the SAMU (Serviço de Atendimento Móvel de Urgência) medical records between January and June 2020. A total of 45,581 calls resulted in mobile units being dispatched during this period. These patients were predominantly male (28,227, 61.9%), with a median age of 47 years (IQR 30-67). The median response time significantly increased during the pandemic, reaching a median of 45.9 min (IQR 30.6-67.7) (p < 0.001). EMS calls were reduced for trauma patients and increased for other medical emergencies, especially respiratory conditions, concomitantly to an escalation in the number of deaths caused by SARS and COVID-19 (p < 0.001). The employment of advanced life support ambulances was higher during the pandemic phase (p = 0.0007). The COVID-19 pandemic resulted in a temporary disorder in the volume and reason for EMS calls in Manaus. Consequently, sensitive indicators like the response time and the employment of advanced life support ambulances were negatively affected. Sudden prehospital EMS pattern changes could play an important role in health surveillance systems, allowing for earlier establishment of countermeasures in epidemics. The impact of the COVID-19 pandemic on prehospital EMS and its role in health surveillance should be further explored.

The economywide recovery measures in Rwanda during the COVID-19 pandemic: How useful a lesson?

In response to the COVID-19 pandemic, governments in many low- and middle-income countries (LMICs) immediately introduced strict public health measures to contain the spread of infection. The economic consequences of these measures were negative and often large in magnitude, necessitating the rapid introduction of economic relief and recovery measures to reinvigorate economic growth and safeguard affected households. Rwanda stands out among other LMICs both for its effective public health policy response and its adaptive economic policy response to COVID-19. Using a dynamic computable general equilibrium (CGE) model of Rwanda, this paper assesses the economywide and welfare impacts of these policy measures and contextualizes results within the overall policy response to COVID-19. Modeling results generated at an early stage of Rwanda’s pandemic experience indicated that relief and recovery measures introduced in 2020 could mitigate COVID-19′s recessionary effects by about 0.8 % points of total GDP, help to recover about 115,000 jobs and, through cash transfers, significantly reduce income losses among poorer households, with total benefits from the measures exceeded their cost by a ratio of 2.2. These results demonstrate the widely replicable value of economywide modeling when used in a timely manner and when positioned within a policymaking process.

Did the COVID-19 quarantine policies applied in Cochabamba, Bolivia mitigated cases successfully? an interrupted time series analysis

ABSTRACT Background The COVID-19 pandemic prompted varied policy responses globally, with Latin America facing unique challenges. A detailed examination of these policies’ impacts on health systems is crucial, particularly in Bolivia, where information about policy implementation and outcomes is limited. Objective To describe the COVID-19 testing trends and evaluate the effects of quarantine measures on these trends in Cochabamba, Bolivia. Methods Utilizing COVID-19 testing data from the Cochabamba Department Health Service for the 2020–2022 period. Stratified testing rates in the health system sectors were first estimated followed by an interrupted time series analysis using a quasi-Poisson regression model for assessing the quarantine effects on the mitigation of cases during surge periods. Results The public sector reported the larger percentage of tests (65%), followed by the private sector (23%) with almost double as many tests as the public-social security sector (11%). In the time series analysis, a correlation between the implementation of quarantine policies and a decrease in the slope of positive rates of COVID-19 cases was observed compared to periods without or with reduced quarantine policies. Conclusion This research underscores the local health system disparities and the effectiveness of stringent quarantine measures in curbing COVID-19 transmission in the Cochabamba region. The findings stress the importance of the measures’ intensity and duration, providing valuable lessons for Bolivia and beyond. As the global community learns from the pandemic, these insights are critical for shaping resilient and effective health policy responses.

Fragmentation in One Health policy and practice responses to antimicrobial resistance and the salutary value of collaborative humility

This paper investigates One Health (OH) applied to antimicrobial resistance (AMR) to deepen and nuance its conceptual underpinnings and inform effective implementation. We consider how models of OH and AMR wedded to bioscience assumptions of life obscure biosocial complexity and reinforce the misleading assumption that scientific knowledge of AMR is generated outside social systems. With reference to in-depth interviews with medical practitioners, scientists and policy-makers working on AMR in Australia and the UK, we explore accounts of OH action on AMR. We show that the implementation of OH is subject to some fragmentation due to workforce organisation, funding arrangements and the absence of detailed guidance for translating OH into practice. Despite OH aspirations for transdisciplinary cooperation and innovation, human-centrism and somewhat incommensurable professional and scientific views on OH constrain trust in the policy approach and limit effective action. We discuss how, in some settings, OH action on AMR does resemble policy aspirations when emphasis is placed on collaborative humility, a finding that underlines OH’s biosocial character. We argue for the development of more robust biosocial models of OH to guide its application to AMR in real world settings.

It’s time for change: inequities and determinants of health-related quality of life among gender and sexually diverse young people in Australia

PurposeThis study was guided by three research aims: firstly, to examine the longitudinal trends of health-related quality of life (HR-QoL) among gender and sexuality diverse (LGBTQA2S+) young people through adolescence (ages 14–19); secondly, to assess longitudinal associations between poor mental health and HR-QoL among LGBTQA2S+ young people through adolescence; and thirdly, to examine differences in HR-QoL among LGBTQA2S+ young people during early adolescence (ages 14 and 15) depending on select school-, peer-, and parent-level factors.MethodsThis study used three of nine available waves of data from a large population-level, probability sample-based, longitudinal cohort study, namely the K′ cohort: children aged 4–5 years old at time of study enrolment followed-up biennially (~ 61% retention rate). HR-QoL weighted means and standard deviations were calculated using Child Health Utility 9D (CHU-9D) scores for LGBTQA2S+ participants at ages 14 and 15 (Wave 6), ages 16 and 17 (Wave 7), and ages 18 and 19 (Wave 8). To strategically identify policy-relevant modifiable behavioural factors suitable for prevention and early intervention, non-parametric Wilcoxon signed-rank tests tested differences in mean CHU-9D ranks at ages 14 and 15 (Wave 6) between groups (gender identity: trans vs. cis; identity-level sexuality: gay, lesbian, bisexual, or other diverse sexuality vs. heterosexual; group-level sexuality: sexually diverse vs. not sexually diverse) and selected school factors (school acceptance, belonging, freedom of expression), peer factors (peer relationship quality, trust, respect), and family factors (parental acceptance, understanding, trust), with Hedge’s g correction statistics computed for effect sizes. Longitudinal associations between gender, sexuality, and poor mental health (depressive symptoms, anxiety, symptoms, self-harm thoughts/behaviour, and suicidal thoughts/behaviour) and HR-QoL were tested using mixed-effects models with random intercepts and random slopes for nested clustering (participants within postcodes).ResultsHR-QoL disparities disproportionately affecting LGBTQA2S+ groups relative to their cisgender, heterosexual peers, were well-established by age 14 to 15 relatively steeper reductions in HR-QoL were observed throughout adolescence among all LGBTQA2S+ groups, with HR-QoL widening the most for trans participants. Poor mental health was significantly associated with HR-QoL declines. LGBTQA2S+ participants with positive school- and parent factors related to feelings of acceptance, belonging, and freedom of self-expression, reported significantly higher HR-QoL during early adolescence.ConclusionEvidence-based public health policy responses are required to address the dire HR-QoL inequities among LGBTQA2S+ young people, particularly trans young people. Prioritising the promotion of school- and family-based interventions which foster LGBTQA2S+ inclusivity, acceptance, and a sense of belonging from early adolescence through young adulthood, represents a feasible, evidence-based, and cost-effective response to address these HR-QoL disparities

Identification of patients undergoing chronic kidney replacement therapy in primary and secondary care data: validation study based on OpenSAFELY and UK Renal Registry

ObjectiveTo validate primary and secondary care codes in electronic health records to identify people receiving chronic kidney replacement therapy based on gold standard registry data.DesignValidation study using data from OpenSAFELY...

The lived experience of people affected by cancer: A global cross-sectional survey protocol.

A diagnosis of cancer impacts the person's physical and mental health and the psychosocial and financial health of their caregivers. While data on the experience of living with cancer is available, there is a dearth of data from persons in low- and middle-income countries (LMICs). The perspectives of other impacted individuals also remain understudied (e.g., bereaved family members), as well as the impact on survivors and their families over time. The objective of this study is to describe the psychosocial and financial impact of cancer on people diagnosed with cancer as a child, adolescent or adult, their families/caregivers, and the family members of those who have died from cancer, in high-income countries (HICs) and LMICs. This study is an observational, descriptive, quantitative study. Data will be collected anonymously via a digital online cross-sectional survey distributed globally by the World Health Organization (WHO) via the LimeSurvey software. Participants will include (a) adults aged 18+ who have been diagnosed with cancer at any age, who are currently undergoing cancer treatment or who have completed cancer treatment; (b) adult family members of individuals of any age with a cancer diagnosis, who are currently undergoing cancer treatment or who have completed cancer treatment; and (c) bereaved family members. Participants will be anonymously recruited via convenience and snowball sampling through networks of organisations related to cancer. Survey results will be analysed quantitatively per respondent group, per time from diagnosis, per disease and country. Results will be disseminated in peer-reviewed journals and at scientific conferences; a summary of results will be available on the WHO website. This study will suggest public health interventions and policy responses to support people affected by cancer and may also lead to subsequent research focusing on the needs of people affected by cancer.

A scoping study on the social determinants of health and sugar consumption in the context of policy approaches for improving population health.

To conduct a scoping review of existing research on the social determinants of health, sugar consumption and public health policy responses to address or improve health outcomes. A total of 13 categories were developed to reflect the authors' interest in the overall focus on the social determinants of health, sugar as an independent risk factor, upstream policy action ('whole populations'), downstream policy action ('targeted') and two contemporary policy strategies (namely 'Vulnerable populations' and 'Proportionate Universalism'). The search strategy was then performed on MEDLINE (via Ovid) and Web of Science, and was limited to the English language. No time limits prior to when the database search was conducted in 2022 were set to explore the full extent of the literature in this field. Five hundred and sixty articles were retrieved, of which 181 met the criteria for review. When all categories were applied, the findings showed that 76% of papers focusing on sugar consumption as a risk factor for non-communicable diseases (NCDs) mentioned the social determinants of health. The majority of studies (60%) recommended downstream interventions, with 40% recommending 'upstream' interventions. A limited proportion (12%) of research work was published in dental journals. Research had been done using predominantly quantitative methods (66% of articles), with 24% of studies adopting a mixed methods approach, and 8% being exclusively qualitative. Research on contemporary strategies for sugar reduction were focused on the 'Global North' and 98% of papers used individual level data focused on targeted approaches, highlighting that there is little direct evidence for contemporary strategies aimed at reducing sugar consumption. Whilst the majority of public and dental health research argues that there is a need to address the social determinants of health, the findings from this study highlight that very few empirical studies have been designed to directly inform contemporary strategies for sugar reduction. More research is therefore needed that can directly assess the evidence for contemporary strategies in public health policy.

Justice implications ofhealth andfood security policies forIndigenous peoples facing COVID-19: a qualitative study andpolicy analysis inPeru.

The spread of COVID-19 in Peru resulted in the declaration of a national health emergency, in which Indigenous peoples were identified as being particularly vulnerable due to their pre-existing poor health indicators and disadvantaged social conditions. The aim of this paper is to examine how the Peruvian government responded to the health and food needs of the Shawi and Ashaninka Indigenous peoples of Peru during the first 18 months of the pandemic (March 2020-August 2021). This study uses both official policy documents and real-world experiences to evaluate policy responses in terms of their immediate impact and their longer-term sustainability and contribution to the improvement of health, well-being and justice for Indigenous communities. Four health and food security responses were evaluated: the Amazon Health Plan and Indigenous Command; food aid; cash aid; and COVID-19 vaccination. We employed the Multidimensional Injustice Framework to analyse the justice implications of the design and implementation of responses. Data collection included 71 interviews with government officials (n = 7), Indigenous leaders (n = 31) and community members (n = 33). The results show how national and regional governments released policies to address the health and food needs of Indigenous peoples directly or indirectly, as part of a broader focus on vulnerable people. However, justice implications were not sufficiently addressed in the design or implementation of the responses. On the distributive dimension, Indigenous communities were prioritized to receive health goods and services, nevertheless, the distribution had shortcomings that impeded their collection and Indigenous food systems and livelihoods were largely overlooked. On the procedural dimension, Indigenous representatives were included to provide culturally sensitive feedback on health interventions, but without funding, and furthermore, the community members had only passive participation. This paper points out the importance of considering and addressing justice implications for more effective and fairer health and food policy responses to current and future health crises.

The global economic impacts of the COVID-19 pandemic

The COVID-19 global pandemic has caused significant global economic and social disruption. We use global data on cases and deaths, and public health and economic policy responses to the pandemic, to illustrate the alternative past and potential future trajectories of the pandemic. Shocks to labor and sectoral productivity, consumption, government expenditure, and country and sector risk premia are used within a global multisectoral intertemporal general equilibrium model: G-Cubed, to assess the economic impacts of COVID-19 under those scenarios. We illustrate the vital role of public health responses in managing a pandemic and restoring confidence among economic agents. The role of global coordination amidst a pandemic is also highlighted. We also compare the GDP projections under the alternative scenarios with the actual GDP outcomes in 2020 and 2021. Despite the uncertainties regarding the health outcomes of COVID-19 and the health and economic policy responses to the pandemic, we demonstrate that the actual outcomes lie within those projected for the scenarios.

Health, economic growth, and Gini index in North America using a panel model

Objective: The objective of this paper is assessed the nexus among health status, economic growth, and the Gini index in North America and its countries using a panel model. Materials and Method: The materials consist of annual data regarding life expectancy, government health expenditure as percentage of the gross domestic product, Gini index, and gross domestic product at constant 2015 US$ for the period 2000-2019. The method applies a panel model for North America and its three countries: Canada, Mexico and The United States. North America diversity treatment among countries is dealt with fixed and random effects. Results: North America inhabitants health status are negatively influenced by an increasing income inequality, and a reduction on economic growth. The country that expends more in health care is The United States, follow by Canada and Mexico. The biggest reduction on life expectancy from an increase in income inequality is in The United States, followed by Canada and Mexico. Life expectancy increases when Canada and The United States experience economic growth. The countries with inarticulate health policy responses to an increase in income inequality are first Mexico followed by The United States. Conclusions: In North America and its countries an increasing income inequality reduces life expectancy, and government health expenditure. Economic growth benefits life expectancy and government health expenditure. Health status seems to improve with a reduction in income inequality and a greater public health expenditure. Therefore, policies that increases income inequality and reduces public health expenditure seems to be advocates of a reduction: in health status, population welfare and economic growth.

Spatial Variation in COVID-19 Mortality in New York City and Its Association with Neighborhood Race, Ethnicity, and Nativity Status.

We examined the association between variation in COVID-19 deaths and spatial differences in the racial, ethnic, and nativity-status composition of New York City neighborhoods, which has received little scholarly attention. Using COVID-19 mortality data (through 31 May 2021) and socioeconomic and demographic data from the American Community Survey at the Zip Code Tabulation Area level as well as United-Hospital-Fund-level neighborhood data from the Community Health Survey of the New York City Department of Health and Mental Hygiene, we employed multivariable Poisson generalized estimating equation models and assessed the association between COVID-19 mortality, racial/ethnic/nativity-status composition, and other ecological factors. Our results showed an association between neighborhood-level racial and ethnic composition and COVID-19 mortality rates that is contingent upon the neighborhood-level nativity-status composition. After multivariable adjustment, ZCTAs with large shares of native-born Blacks and foreign-born Hispanics and Asians were more likely to have higher COVID-19 mortality rates than areas with large shares of native-born Whites. Areas with more older adults and essential workers, higher levels of household crowding, and population with diabetes were also at high risk. Small-area analyses of COVID-19 mortality can inform health policy responses to neighborhood inequalities on the basis of race, ethnicity, and immigration status.

SARS-CoV-2 omicron spike simulations: broad antibody escape, weakened ACE2 binding, and modest furin cleavage.

The recent emergence of the omicron variant of the SARS-CoV-2 virus with large numbers of mutations has raised concern about a potential new surge in infections. Here we use molecular dynamics to study the biophysics of the interface of the BA1 and BA2 omicron spike protein binding to (i) the ACE2 receptor protein, (ii) antibodies from all known binding regions, and (iii) the furin binding domain. Our simulations suggest that while there is a significant reduction of antibody (Ab) binding strength corresponding to escape, the omicron spikes pay a cost in terms of weaker receptor binding as measured by interfacial hydrogen bonds (H-bond). The furin cleavage domain (FCD) is the same or weaker binding than the delta variant, suggesting lower fusogenicity resulting in less viral load and disease intensity than the delta variant. IMPORTANCE The BA1 and BA2 and closely related BA2.12.2 and BA.5 omicron variants of SARS-CoV-2 dominate the current global infection landscape. Given the high number of mutations, particularly those which will lead to antibody escape, it is important to establish accurate methods that can guide developing health policy responses that identify at a fundamental level whether omicron and its variants are more threatening than its predecessors, especially delta. The importance of our work is to demonstrate that simple in silico simulations can predict biochemical binding details of the omicron spike protein that have epidemiological consequences, especially for binding to the cells and for fusing the viral membrane with the cells. In each case, we predicted weaker binding of the omicron spike, which agreed with subsequent experimental results. Future virology experiments will be needed to test these predictions further.

Pathways from climate change to emotional wellbeing: A qualitative study of Kenyan smallholder farmers living with HIV.

Climate change is associated with adverse mental and emotional health outcomes. Social and economic factors are well-known drivers of mental health, yet comparatively few studies examine the social and economic pathways through which climate change affects mental health. There is additionally a lack of research on climate change and mental health in sub-Saharan Africa. This qualitative study aimed to identify potential social and economic pathways through which climate change impacts mental and emotional wellbeing, focusing on a vulnerable population of Kenyan smallholder farmers living with HIV. We conducted in-depth, semi-structured interviews with forty participants to explore their experience of climate change. We used a thematic analytical approach. We find that among our study population of Kenyan smallholder farmers living with HIV, climate change is significantly affecting mental and emotional wellbeing. Respondents universally report some level of climate impact on emotional health including high degrees of stress; fear and concern about the future; and sadness, worry, and anxiety from losing one's home, farm, occupation, or ability to support their family. Climate-related economic insecurity is a main driver of emotional distress. Widespread economic insecurity disrupts systems of communal and family support, which is an additional driver of worsening mental and emotional health. Our study finds that individual adaptive strategies used by farmers in the face of economic and social volatility can deepen economic insecurity and are likely insufficient to protect mental health. Finally, we find that agricultural policies can worsen economic insecurity and other mental health risk factors. Our proposed conceptual model of economic and social pathways relevant for mental health can inform future studies of vulnerable populations and inform health system and policy responses to protect health in a changing climate.

Preparing for the unexpected: a comparative study of policies addressing post-terror health reactions in Norway and France

BackgroundIn the wake of terrorist attacks, protecting the health and psychosocial wellbeing of those affected and the general population, are important tasks for the healthcare system. The responses to such emergencies are often complex, including different phases and many actors, and may unveil insufficiencies that incite reforms to existing systems. Recently, initiatives have been promoted to strengthen cooperation and coordination regarding the governance of health threats in Europe. Comparative research is requested on how states prepare for health emergencies such as terrorist attacks. This study investigated how governments in two European countries with universal health coverage prepared to address the civilian population’s health needs after terrorist attacks, and the factors that contributed to shaping their chosen approach.MethodsUtilizing document analysis and Walt and Gilson’s model for the analysis of health policy, national plans for post-terror health responses in Norway and France were studied with a focus on context, process, content, and actors.ResultsWhereas target groups for psychosocial care and certain measures were similar in both cases, the contents of prescribed policies and the actors responsible for enacting them differed. One of the most distinct differences was to what extent specialized mental healthcare was relied upon to provide psychosocial follow-up in the emergency phase. In the French approach, specialized mental healthcare practitioners, such as psychiatrists, psychologists and psychiatric nurses, provided early psychosocial support. In contrast, the Norwegian approach relied on interdisciplinary primary care crisis teams in the local municipalities to provide early psychosocial support, with further involvement of specialized mental healthcare if this was considered necessary. Historical, political, and systemic differences contributed to the variation in the countries’ responses.ConclusionsThis comparative study highlights the complexity and diversity of health policy responses to terrorist attacks across countries. Moreover, challenges and opportunities for research and health management in response to such disasters, including possibilities and potential pitfalls for the coordination of this work across Europe. An important first step could be to map out existing services and practices across countries to better understand if and how common core elements for psychosocial follow-up might be implemented internationally.

COVID-19: Epidemiological Models

The world has been confronted in recent decades with several infectious disease outbreaks caused by novel pathogens, with the COVID-19 pandemic being the most severe of these. In this article, I review some of the main elements of epidemiological models used to forecast the trajectory of a new epidemic and to guide public health policy responses to a new infectious disease. I argue that economists have a lot to contribute to the discussion of public health policies, particularly in regard to assessing the costs and benefits of alternative policies and in improving the modeling of changes in human behavior in response to new infectious diseases. This survey is intended to serve economists interested in starting research in these areas.

Coronavirus pandemic in the South Asia region: Health policy and economy trade-off

The South Asian Association for Regional Cooperation (SAARC) covers Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka. We conducted a comparative analysis of the trade-off between the health policies for the prevention of COVID-19 spread and the impact of these policies on the economies and livelihoods of the South Asia populations. We analyzed COVID-19 data on epidemiology, public health and health policy, health system capacity, and macroeconomic indicators from January 2020 to March 2021 to determine temporal trends by conducting joinpoint regression analysis using average weekly percent change (AWPC). Bangladesh had the highest statistically significant AWPC for new COVID-19 cases (17.0; 95% CI = 7.7-27.1, P < 0.001), followed by the Maldives (12.9; 95% CI = 5.3-21.0, P < 0.001) and India (10.0; 95% CI = 8.4-11.5, P < 0.001). The AWPC for COVID-19 deaths was significant for India (6.5; 95% CI = 4.3-8.9, P < 0.001) and Bangladesh (6.1; 95% CI = 3.7-8.5, P < 0.001). Nepal (55.79%), and India (34.91%) had the second- and third-highest increase in unemployment, while Afghanistan (6.83%) and Pakistan (16.83%) had the lowest. The rate of change of real GDP had the highest decrease for Maldives (557.51%), and India (297.03%); Pakistan (46.46%) and Bangladesh (70.80%), however, had the lowest decrease. The government response stringency index for Pakistan had a see-saw pattern with a sharp decline followed by an increase in the government health policy restrictions that approximated the test-positivity trend. Unlike developed economies, the South Asian developing countries experienced a trade-off between health policy and their economies during the COVID-19 pandemic. South Asian countries (Nepal and India), with extended periods of lockdowns and a mismatch between temporal trends of government response stringency index and the test-positivity or disease incidence, had higher adverse economic effects, unemployment, and burden of COVID-19. Pakistan demonstrated targeted lockdowns with a rapid see-saw pattern of government health policy response that approximated the test-positivity trend and resulted in lesser adverse economic effects, unemployment, and burden of COVID-19.

The COVID-19 shock and consumer credit: Evidence from credit card data

We study the dynamic effect of the COVID-19 shock on credit card use in 2020. Local case incidence had a strong negative effect on credit card spending in the early months of the pandemic, which diminished over time. This time-varying pattern was driven by the fear of the virus, rather than government support programs, consistent with the “pandemic fatigue” of consumers. Local pandemic severity also had a strong effect on credit card repayments. These spending and repayment effects offset each other, resulting in no effect on credit card borrowing, consistent with credit-smoothing behavior. The local stringency of nonpharmaceutical interventions also had a negative effect on spending and repayments, albeit smaller in magnitude. We conclude that the pandemic itself was a more important driver of changes in credit card use than the public health policy response.

COVID-19 and human resources for health: analysis of planning, policy responses and actions in Latin American and Caribbean countries

BackgroundThe COVID-19 pandemic led to worldwide health service disruptions, due mainly to insufficient staff availability. To gain insight into policy responses and engage with policy-makers, the World Health Organization (WHO) developed a global approach to assess and measure the impact of COVID-19 on the health workforce. As part of this, WHO, together with the Pan American Health Organization (PAHO), supported an impact analysis of COVID-19 on health workers and policy responses, through country case studies in Latin America and the Caribbean (LAC).MethodsWe sought to identify lessons learned from policies on human resources for health (HRH) during health emergencies, to improve HRH readiness. First, we performed a rapid literature review for information-gathering. Second, we used the WHO interim guidance and impact measurement framework for COVID-19 and HRH to systematically organize that information. Finally, we used the Health Labour Market Framework to guide the content analysis on COVID-19 response in eight LAC countries and identify lessons learned to improve HRH readiness.ResultsPlanning and implementing the COVID-19 response required strengthening HRH governance and HRH data and information systems. The results suggest two main aspects for HRH governance crucial to enabling an agile response: (1) aligning objectives among ministries to define and produce regulation and policy actions; and (2) agreeing on the strategy for HRH management between the public and private sectors, and between central and local governments. We identified three areas for improvement: (a) HRH information systems; (b) methodologies to estimate HRH needs; and (c) teams to analyse information for decision-making. Three key actions were identified during countries monitored, reviewed, and updated their response stages: (i) strengthening response through primary health care; (ii); planning HRH needs to implement the vaccination plan; and (iii) securing long-term HRH availability.ConclusionCountries coordinated and articulated with different stakeholders to align objectives, allocate resources, and agree on policy actions to implement the COVID-19 response. Data and information for HRH preparedness and implementation were key in enabling an agile COVID-19 response and are key areas to explore for improved pandemic preparedness.

Using weather factors and google data to predict COVID-19 transmission in Melbourne, Australia: A time-series predictive model

BackgroundForecast models have been essential in understanding COVID-19 transmission and guiding public health responses throughout the pandemic. This study aims to assess the effect of weather variability and Google data on COVID-19 transmission and develop multivariable time series AutoRegressive Integrated Moving Average (ARIMA) models for improving traditional predictive modelling for informing public health policy. MethodsCOVID-19 case notifications, meteorological factors and Google data were collected over the B.1.617.2 (Delta) outbreak in Melbourne, Australia from August to November 2021. Timeseries cross-correlation (TSCC) was used to evaluate the temporal correlation between weather factors, Google search trends, Google Mobility data and COVID-19 transmission. Multivariable time series ARIMA models were fitted to forecast COVID-19 incidence and Effective Reproductive Number (Reff) in the Greater Melbourne region. Five models were fitted to compare and validate predictive models using moving three-day ahead forecasts to test the predictive accuracy for both COVID-19 incidence and Reff over the Melbourne Delta outbreak. ResultsCase-only ARIMA model resulted in an R squared (R2) value of 0.942, Root Mean Square Error (RMSE) of 141.59, and Mean Absolute Percentage Error (MAPE) of 23.19. The model including transit station mobility (TSM) and maximum temperature (Tmax) had greater predictive accuracy with R2 0.948, RMSE 137.57, and MAPE 21.26. ConclusionMultivariable ARIMA modelling for COVID-19 cases and Reff was useful for predicting epidemic growth, with higher predictive accuracy for models including TSM and Tmax. These results suggest that TSM and Tmax would be useful for further exploration for developing weather-informed early warning models for future COVID-19 outbreaks with potential application for the inclusion of weather and Google data with disease surveillance in developing effective early warning systems for informing public health policy and epidemic response.