Pandemic Preparedness Research Articles

Assessing the impact of institutional mistrust on parental endorsement for COVID-19 vaccination among school communities in San Diego County, California.

Institutional mistrust has weakened COVID-19 mitigation efforts. Assessing to what extent institutional mistrust impacts parental decision making is important in formulating structural efforts for improving future pandemic response. We hypothesized that institutional mistrust is associated with lower parental endorsement for COVID-19 vaccination. We distributed an online survey among parents from schools in areas with high levels of social vulnerability relative to the rest of San Diego County. We defined vaccination endorsement as having a child aged 5 years or older who received at least one COVID-19 vaccine dose or being very likely to vaccinate their child aged 6 months-4 years when eligible. Institutional mistrust reflected the level of confidence in institutions using an aggregate score from 11 to 44. We built a multivariable logistic regression model with potential confounding variables. Out of 290 parents in our sample, most were female (87.6%), reported their child as Hispanic/Latino (73.4%), and expressed vaccination endorsement (52.1%). For every one-point increase in mistrust score, there was an 8% reduction in the likelihood of participants endorsing vaccination for their child. Other statistically significant correlates that were positively associated with vaccination endorsement included parent vaccination status, child age, parent age, and Hispanic/Latino ethnicity. Our study further demonstrates how institutional mistrust hinders public response during health emergencies. Our findings also highlight the importance of building confidence in institutions and its downstream effects on pandemic preparedness and public health. One way that institutions can improve their relationship with constituents is through building genuine partnerships with trusted community figures.

Long-term wastewater monitoring of SARS-CoV-2 viral loads and variants at the major international passenger hub Amsterdam Schiphol Airport: A valuable addition to COVID-19 surveillance

Wastewater-based epidemiological surveillance at municipal wastewater treatment plants has proven to play an important role in COVID-19 surveillance. Considering international passenger hubs contribute extensively to global transmission of viruses, wastewater surveillance at this type of location may be of added value as well. The aim of this study is to explore the potential of long-term wastewater surveillance at a large passenger hub as an additional tool for public health surveillance during different stages of a pandemic. Here, we present an analysis of SARS-CoV-2 viral loads in airport wastewater by reverse-transcription quantitative polymerase chain reaction (RT-qPCR) from the beginning of the COVID-19 pandemic in Feb 2020, and an analysis of SARS-CoV-2 variants by whole-genome next-generation sequencing from Sep 2020, both until Sep 2022, in the Netherlands. Results are contextualized using (inter)national measures and data sources such as passenger numbers, clinical surveillance data and national wastewater surveillance data. Our findings show that wastewater surveillance was possible throughout the study period, irrespective of measures, as viral loads were detected and quantified in 98.6 % (273/277) of samples. Emergence of SARS-CoV-2 variants, identified in 91.0 % (161/177) of sequenced samples, coincided with increases in viral loads. Furthermore, trends in viral load and variant detection in airport wastewater closely followed, and in some cases preceded, trends in national daily average viral load in wastewater and variants detected in clinical surveillance. Wastewater-based epidemiology at a large international airport is a valuable addition to classical COVID-19 surveillance and the developed expertise can be applied in pandemic preparedness plans for other (emerging) pathogens in the future.

Public perspectives on COVID-19 public health and social measures in Japan and the United Kingdom: a qualitative study

BackgroundThe COVID-19 pandemic, caused by SARS-CoV-2, was one of the greatest modern public health crises that the world has faced. Countries undertook sweeping public health and social measures (PHSM); including environmental actions such as disinfection and ventilation; surveillance and response, such as contact tracing and quarantine; physical, such as crowd control; and restrictions on travel. This study focuses on the public perceptions of PHSM in two countries, Japan and the United Kingdom (UK) as examples of high-income countries that adopted different measures over the course of the pandemic.MethodsThis study was conducted between November 2021 and February 2022, a period in which the Omicron variant of SARS-CoV-2 was predominant. Fourteen online focus group discussions were conducted in each country. Overall, 106 total participants (50 from the UK and 56 from Japan) participated in 23 focus groups (11 in the UK and 12 in Japan) with an average of three to six participants per group. Both countries were compared using a thematic analysis method.ResultsBoth countries’ participants agreed that vaccination was an effective measure. However, they did not favor mandatory vaccination policies. Working from home was well accepted by both sides, but they reported that schools should have continued to be opened as before COVID-19. Both sides of participants expressed that temperature testing alone in indoor facilities was ineffective as a COVID-19 control measure. There were contrasting views on face covering rules in public spaces, international and domestic movement restrictions. High acceptance of mask-wearing was reflective of Japanese customs, while it was accepted as a strong recommendation for participants in the UK. Japanese participants favored quarantine for international travel, while the UK participants supported banning non-essential travel.ConclusionSimilar and contrasting views on PHSM against COVID-19 between Japan and the UK demonstrated how policies in controlling an epidemic should be tailored by country with respect to its norms, cultures, economic and disease burden. Our findings may guide how policy makers can engage with the public through effective health communication and consider regulations that are aligned with the public’s views and capacities in changing their behavior for future pandemic preparedness.

How Political Ideology and Media Shaped Vaccination Intention in the Early Stages of the COVID-19 Pandemic in the United States

As a pharmaceutical intervention, vaccines remain a major public health strategy for mitigating the effects of COVID-19. Yet, vaccine intake has been affected by various cognitive and cultural factors. We examine how a selected set of factors (i.e., knowledge, concern, media, peer influence, and demographics) shaped COVID-19 vaccination intention in the early phase of the pandemic (Fall 2020). Using a survey conducted in three US states (Idaho, Texas, and Vermont) just prior to the rollout of the first vaccines against COVID-19, we find that COVID-19 concern was the primary driver of vaccination intention. Concern was shaped mainly by two factors: political ideology and media sources. Yet, ideology and media were much more important in affecting concern for those who leaned politically conservative, as opposed to those who leaned liberal or remained moderate. The results from our structural equation models affirm that the information politically conservative respondents were receiving reinforced the effects of their ideology, leading to a greater reduction in their concern. We discuss the potential implications of these findings for future pandemic preparedness.

COVID-19 Pandemic Experiences of Families in Which a Child/Youth Has Autism and Their Service Providers: Perspectives and Lessons Learned.

The impacts of the COVID-19 pandemic on autistic children/youth and their families and on service providers are not yet well-understood. This study explored the lived experiences of families with an autistic child and service providers who support them regarding the impacts of the pandemic on service delivery and well-being. In this qualitative study, families and service providers (e.g., early intervention staff, service providers, school personnel) supporting autistic children/youth were interviewed. Participants were recruited from a diagnostic site and two service organizations that support autistic children/youth. Thirteen parents and 18 service providers participated in either an individual or group interview. Findings indicate challenges associated with pandemic restrictions and resulting service shifts. These challenges generally imposed negative experiences on the daily lives of autistic children/youth and their families, as well as on service providers. While many were adversely affected by service delivery changes, families and service agencies/providers pivoted and managed challenges. Shifts have had varied impacts, with implications to consider in pandemic planning and post-pandemic recovery. Results highlight the need for autism-focused supports, as well as technology and pandemic preparedness capacity building within health, therapeutic and educational sectors in order to better manage shifts in daily routines during emergencies such as a pandemic. Findings also offer instructive consideration in service delivery post-pandemic.

Types of COVID-19 Disaster Work and Psychological Responses in National Guard Service Members.

The National Guard (NG) served as a critical component of the U.S. response to the coronavirus disease 2019 pandemic. Understanding the impact of types of pandemic-related disaster work on mental health responses can aid in sustaining NG service members' health and preparation for subsequent activations and future pandemics. We surveyed 1,363 NG unit (NGU) service members (88% Army; 80% enlisted; 32% 30 to 39 years old; 84% male) following activation in response to the pandemic. Surveys were administered between August and December 2020, which was approximately 2 to 3 months post-activation. Surveys assessed overall activation stress, participation in different types of disaster work, probable post-traumatic stress disorder (PTSD), anxiety and depression, and anger. A disaster work stress scale assessed different types of disaster work during activation and associated stress levels. For each individual, we calculated an overall work task stress (WTS) scaled score, with a maximum score of 100. Logistic regression analyses were conducted to examine the relationship of high-stress disaster work tasks to post-activation PTSD, anxiety and depression, and anger, adjusting for socio-demographic and service-related variables. The study was approved by the Institutional Review Board of the Uniformed Services University (USU) in Bethesda, MD. Among NGU service members, 12.7% (n = 172) described their activation as very/extremely stressful. The work tasks with the highest scaled scores were as follows: (1) Patient transportation (WTS scaled score = 100); (2) working with the dead (WTS = 82.2); and (3) working with families of coronavirus disease 2019 patients (WTS = 72.7). For each individual's work tasks, we identified the work task associated with the highest WTS score. The top one-third of WTS scores were classified as the high-stress group. Approximately 9% of participants (n = 111) had probable PTSD, 6.7% (n = 85) had clinically significant anxiety and depression, and 12.3% (n = 156) had high anger. Multivariable logistic regression analyses, adjusting for covariates, found that NGU service members exposed to the highest level of disaster WTS were more likely to report PTSD (odds ratio [OR] = 1.48 [95% confidence interval [CI] = 1.13-1.94], χ2 = 7.98), anxiety and depression (OR = 1.91 [95% CI = 1.17-3.13]; χ2 = 6.67), and anger (OR = 1.63 [95% CI = 1.13-2.37]; χ2 = 6.66) post-activation. Identifying work tasks associated with high levels of stress can help detect individuals at risk for adverse mental health responses post-exposure. Distinguishing features of high-stress work conditions can be generalized to other types of work conditions and disaster response and are important targets for planning and preventive efforts.

Preparing for pandemic response in the context of limited resources

AbstractPandemics are outbreaks of an infectious disease that increase morbidity and mortality over a wide geographic area. These events require large‐scale interventions from governments and health agencies to curtail transmission within a population. In assessing the impact of these interventions, policymakers avail themselves of simulations from compartmental models. However, it is commonplace that modellers employ fixed fractions to represent interventions, which implicitly assume that resources instantaneously and boundlessly adjust to the desired target and may predict overly optimistic outcomes. Here, we propose a model that integrates four crucial countermeasures subject to resource constraints. We present this structure utilising the concept of small models and frame the simulations in the context of a hypothetical spread of influenza in the Netherlands, drawing on empirical data. After incorporating resource constraints, we find that only a comprehensive response controls the disease. These findings highlight the need for improving strategic plans to support pandemic preparedness. © 2024 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

Covid-19: Lessons from the pandemic in sub-Saharan Africa relevant to the WHO IA2030 vaccination agenda

While the global need to promote vaccination against viral illnesses is recognized, there are fundamental reasons for the failure of many programs. The World Health Organization has emphasized that the causes of low vaccine use must be understood and addressed in order to increase people’s demand for immunization services, and such understanding is central to promoting vaccine acceptance, as called for in the current WHO IA2030 initiative. Immunization programs remain fundamental to both pandemic preparedness and robust health systems. But, to achieve the goals of IA2030 requires improved targeting and reach to protect against viral illness and other global pathogens, hence the need for creative and innovative community engagement to increase vaccine uptake, and the relevance of learning from past pandemics. In sub-Saharan Africa, important lessons were learned during the Covid-19 pandemic; many of these are now broadly applicable to enhance current programs to promote vaccine acceptance such as the WHO IA2030 initiative. Strategies that helped increase vaccine uptake in Africa included six approaches to health promotion called for by the 2017 Lancet Commission on the future of health in sub-Saharan Africa. (Adoption of a community empowerment approach; Use of inclusive, people-centered strategies; Provision of innovative education; Creation of novel and improved tools; Training personnel to be mindful of, and responsive to, local needs; and Endorsement of non-traditional avenues to engage and inform). This commentary describes the principles underlying these six approaches, and summarizes ways in which their use contributed to programs working to increase vaccine uptake in sub-Saharan Africa that are applicable in a global context.

Beyond "business as usual": lessons from FIFA for fair benefit-sharing in global health.

While researchers and agencies from low- and middle-income countries often contribute significantly to public health surveillance data, which is crucial for effective pandemic prevention, preparedness, and response activities, they often do not receive adequate compensation for their contributions. Incentivizing data sharing is important for informing public health responses to pathogens with pandemic potential. However, existing data-sharing legal frameworks have limitations. In this context, we looked beyond "business as usual" candidates to explore the applicability of a benefit-sharing model developed and implemented by the Fédération Internationale de Football Association (International Federation of Association Football; FIFA) in international association football. This model rewards grassroots contributions and redistributes benefits, promoting a fair balance of interests across diverse economic contexts. We discuss adapting FIFA's mechanisms, including training compensation and solidarity payments, to create a novel benefit-sharing framework in global health. Given the complexity of global health, we note ways in which components of the FIFA model would need to be adapted for global health. Challenges such as integrating into existing legal frameworks, ensuring broad international buy-in, and accommodating different pandemic periods are examined. While adapting the FIFA model presents challenges, it offers a promising approach to achieving more equitable data sharing and benefit distribution in global health.

Analyzing factors affecting positivity in drive-through COVID-19 testing: a cross-sectional study

BackgroundDemand for COVID-19 testing prompted the implementation of drive-through testing systems. However, limited research has examined factors influencing testing positivity in this setting.MethodsFrom October 2020 to March 2023, a total of 1,341 patients, along with their clinical information, were referred from local clinics to the Sasebo City COVID-19 drive-through PCR center for testing. Association between clinical information or factors related to the drive-through center and testing results was analyzed by Fisher’s exact test and logistic regression models.ResultsIndividuals testing positive exhibited higher frequencies of upper respiratory symptoms; cough (OR 1.5 (95% CI 1.2–1.8), p < 0.001, q = 0.005), sore throat (OR 2.4 (95% CI 1.9-3.0), p < 0.001, q < 0.001), runny nose (OR 1.4 (95% CI 1.1–1.8), p = 0.002, q = 0.009), and systemic symptoms; fever (OR 1.5 (95% CI 1.1-2.0), p = 0.006, q = 0.02), headache (OR 1.9 (95% CI 1.4–2.5), p < 0.001, q < 0.001), and joint pain (OR 2.7 (95% CI 1.8–4.1), p < 0.001, q < 0.001). Conversely, gastrointestinal symptoms; diarrhea (OR 0.2 (95% CI 0.1–0.4), p < 0.001, q < 0.001) and nausea (OR 0.3 (95% CI 0.1–0.6), p < 0.001, q < 0.001) were less prevalent among positives. During omicron strain predominant period, higher testing positivity rate (OR 20 (95% CI 13–31), p < 0.001) and shorter period from symptom onset to testing (3.2 vs. 6.0 days, p < 0.001) were observed compared to pre-omicron period. Besides symptoms, contact history with infected persons at home (OR 4.5 (95% CI 3.1–6.5), p < 0.001, q < 0.001) and in office or school (OR 2.9 (95% CI 2.1–4.1), p < 0.001, q < 0.001), as well as the number of sample collection experiences by collectors (B 7.2 (95% CI 2.8–12), p = 0.002) were also associated with testing results.ConclusionsThese findings underscore the importance of factors related to drive-through centers, especially contact history interviews and sample collection skills, for achieving higher rates of COVID-19 testing positivity. They also contribute to enhanced preparedness for next infectious disease pandemics.

Perceptions of policymakers and ethicists on ethical considerations in the conduct of research during disease outbreaks in Nigeria

Background There is a dearth of literature on the perspectives of stakeholders from countries in Africa on the institution of a research culture as part of a holistic system of pandemic preparedness and response. This study aimed to explore the perspectives of policymakers, representatives from Research Ethics Committees (RECs), and international bioethics experts on the ethics of conducting research during infectious disease outbreaks in Nigeria. Methods We conducted structured interviews with six policymakers actively engaged in disease outbreak response. The interview themes included systems and structures for research, local researcher competency, regulatory oversight, study types, ethical review approaches, and integrating research into outbreak response. We further engaged 12 participants including REC members from Nigeria and Liberia, international bioethics experts, and study co-investigators in a structured discussion to appraise and expand on themes identified during the interviews at a 2-day meeting in December 2018. We also held two virtual consultations afterwards. The findings from these processes were synthesized to develop a comprehensive report. Results Participants stressed the significance of conducting research during disease outbreaks to understand causal factors, evaluate public health measures, and inform future prevention and treatment strategies, and identified the need for clear ethical guidelines for RECs during outbreaks. Participants proposed a sliding scale for prioritizing categorized studies, emphasizing immediate solutions over future-focused research. Discussants proposed a "systems approach" to ethics review, emphasizing interdependence, governance structures, communication infrastructure, effective communication with policymakers, and a funding structure. Conclusion Conducting ethical research during disease outbreaks requires a comprehensive, context-dependent approach, involving stakeholders, and ensuring robust ethical oversight through proficient RECs. The proposed "System Approach" offers a model for sustainable and effective ethics review during outbreaks, fostering locally relevant and socially valuable research while prioritizing the well-being of research participants and communities.

Medical resource usage for COVID-19 evaluated using the National Database of Health Insurance Claims and Specific Health Checkups of Japan.

The coronavirus disease 2019 (COVID-19) pandemic exhibited several different waves threatening global health care. During this pandemic, medical resources were depleted. However, the kind of medical resources provided to each wave was not clarified. This study aimed to examine the characteristics of medical care provision at COVID-19 peaks in preparation for the next pandemic. Using medical insurance claim records in Japan, we examined the presence or absence of COVID-19 infection and the use of medical resources for all patients monthly by age group. The wave around August 2021 with the Delta strain had the strongest impact on the working population in terms of hospital admission and respiratory support. For healthcare providers, this peak had the highest frequency of severely ill patients. In the subsequent wave, although the number of patients with COVID-19 remained high, they were predominantly older adults, with relatively fewer patients receiving intensive care. In future pandemics, we should refer to the wave around August 2021 as a situation of medical resource shortage resulting from the COVID-19 pandemic.

Social contacts in Switzerland during the COVID-19 pandemic: Insights from the CoMix study

To mitigate the spread of SARS-CoV-2, the Swiss government enacted restrictions on social contacts from 2020 to 2022. In addition, individuals changed their social contact behavior to limit the risk of COVID-19. In this study, we aimed to investigate the changes in social contact patterns of the Swiss population. As part of the CoMix study, we conducted a survey consisting of 24 survey waves from January 2021 to May 2022. We collected data on social contacts and constructed contact matrices for the age groups 0–4, 5–14, 15–29, 30–64, and 65 years and older. We estimated the change in contact numbers during the COVID-19 pandemic to a synthetic pre-pandemic contact matrix. We also investigated the association of the largest eigenvalue of the social contact and transmission matrices with the stringency of pandemic measures, the effective reproduction number (Re), and vaccination uptake. During the pandemic period, 7084 responders reported an average number of 4.5 contacts (95% confidence interval, CI: 4.5–4.6) per day overall, which varied by age and survey wave. Children aged 5–14 years had the highest number of contacts with 8.5 (95% CI: 8.1–8.9) contacts on average per day and participants that were 65 years and older reported the fewest (3.4, 95% CI: 3.2–3.5) per day. Compared with the pre-pandemic baseline, we found that the 15–29 and 30–64 year olds had the largest reduction in contacts. We did not find statistically significant associations between the largest eigenvalue of the social contact and transmission matrices and the stringency of measures, Re, or vaccination uptake. The number of social contacts in Switzerland fell during the COVID-19 pandemic and remained below pre-pandemic levels after contact restrictions were lifted. The collected social contact data will be critical in informing modeling studies on the transmission of respiratory infections in Switzerland and to guide pandemic preparedness efforts.

Urgent pandemic messaging of WHO, World Bank, and G20 is inconsistent with their evidence base

AbstractWhen international agencies make claims of an “existential threat” to humanity and advocate for urgent action from countries, it should be a safe assumption that they are consistent with their own data. However, a review of the data and evidentiary citations underlying the claims of the World Health Organization (WHO), the World Bank, and the Group of Twenty (G20) reveals a troubling picture in which the stated urgency and burden of infectious disease outbreaks, namely those of pandemic threat, is grossly misrepresented. These discrepancies in key documents and subsequent recitations in pandemic preparedness proposals have significant policy and financial implications. Disproportionate pandemic preparedness based on these false premises risks a significant opportunity cost through unnecessary diversion of financial and political resources away from global health priorities of higher burden. As WHO Member States plan to transform the way international health emergencies are managed at the World Health Assembly in May 2024, there is a crucial need to pause, rethink, and ensure future policy reflects evidence of need.

Predicting the Spread of a Pandemic Using Machine Learning: A Case Study of COVID-19 in the UAE

Pandemics can result in large morbidity and mortality rates that can cause significant adverse effects on the social and economic situations of communities. Monitoring and predicting the spread of pandemics helps the concerned authorities manage the required resources, formulate preventive measures, and control the spread effectively. In the specific case of COVID-19, the UAE (United Arab Emirates) has undertaken many initiatives, such as surveillance and contact tracing by introducing mobile apps such as Al Hosn, containment of spread by limiting the gathering of people, online schooling and remote work, sanitation drives, and closure of public places. The aim of this paper is to predict the trends occurring in pandemic outbreak, with COVID-19 in the UAE being a specific case study to investigate. In this paper, a predictive modeling approach is proposed to predict the future number of cases based on the recorded history, taking into consideration the enforced policies and provided vaccinations. Machine learning models such as LASSO Regression and Exponential Smoothing, and deep learning models such as LSTM, LSTM-AE, and bi-directional LSTM-AE, are utilized. The dataset used is publicly available from the UAE government, Federal Competitiveness and Statistics Centre (FCSC) and consists of several attributes, such as the numbers of confirmed cases, recovered cases, deaths, tests, and vaccinations. An additional categorical attribute is manually added to the dataset describing whether an event has taken place, such as a national holiday or a sanitization drive, to study the effect of such events on the pandemic trends. Experimental results showed that the Univariate LSTM model with an input of a five-day history of Confirmed Cases achieved the best performance with an RMSE of 275.85, surpassing the current state of the art related to the UAE by over 30%. It was also found that the bi-directional LSTMs performed relatively well. The approach proposed in the paper can be applied to monitor similar infectious disease outbreaks and thus contribute to strengthening the authorities’ preparedness for future pandemics.

Managing disrupted supply chains in Swedish hospitals during the COVID-19 pandemic

ABSTRACT The COVID-19 pandemic has disrupted global supply chains and caused widespread shortages of healthcare supplies. This mixed-methods study examined the management of supply shortages in Swedish hospitals during the COVID-19 pandemic. The key findings are that the shortage of supplies was initially severe owing to low regional and national contingency inventory levels, a lack of knowledge of supply chain management, and cost-saving measures. The perceived consequences of the shortage of personal protective equipment persisted in emergency and inpatient departments, in the later waves. Although pharmaceutical shortages later decreased, hospital managers were disappointed that they persisted. This study also highlights the effectiveness of consensus-based hourly supply agreements between service organisations and unit managers, which makes the prioritisation of the limited supply more dynamic. Despite these challenges, hospitals were able to adapt to the supply chain disruptions caused by the pandemic; however, the results emphasise the importance of preparedness for future pandemics.

Seasonal antigenic prediction of influenza A H3N2 using machine learning

Antigenic characterization of circulating influenza A virus (IAV) isolates is routinely assessed by using the hemagglutination inhibition (HI) assays for surveillance purposes. It is also used to determine the need for annual influenza vaccine updates as well as for pandemic preparedness. Performing antigenic characterization of IAV on a global scale is confronted with high costs, animal availability, and other practical challenges. Here we present a machine learning model that accurately predicts (normalized) outputs of HI assays involving circulating human IAV H3N2 viruses, using their hemagglutinin subunit 1 (HA1) sequences and associated metadata. Each season, the model learns an updated nonlinear mapping of genetic to antigenic changes using data from past seasons only. The model accurately distinguishes antigenic variants from non-variants and adaptively characterizes seasonal dynamics of HA1 sites having the strongest influence on antigenic change. Antigenic predictions produced by the model can aid influenza surveillance, public health management, and vaccine strain selection activities.

Community interventions for pandemic preparedness: A scoping review of pandemic preparedness lessons from HIV, COVID-19, and other public health emergencies of international concern.

Community action is broadly recognised as central to comprehensive and effective system responses to pandemics. However, there is uncertainty about how and where communities can be best supported to bolster long-term resilience and preparedness. We applied a typology of community interventions (Community Informing, Consulting, Involving, Collaborating or Empowering-or CICICE) to cover the diverse range of interventions identified across the literature and used this to structure a scoping review addressing three linked topics: (i) how CICICE interventions have been understood and applied in the literature on epidemic and pandemic preparedness; (ii) the spectrum of interventions that have been implemented to strengthen CICICE and (iii) what evidence is available on their effectiveness in influencing preparedness for current and future emergencies. We drew on peer-reviewed and grey literature from the HIV (from 2000) and COVID-19 pandemics and recent public health emergencies of international concern (from 2008), identified through systematic searches in MEDLINE, Scopus, the Cochrane Collaboration database, supplemented by keyword-structured searches in GoogleScholar and websites of relevant global health organisations. Following screening and extraction, key themes were identified using a combined inductive/deductive approach. 130 papers met the criteria for inclusion. Interventions for preparedness were identified across the spectrum of CICICE. Most work on COVID-19 focused on informing and consulting rather than capacity building and empowerment. The literature on HIV was more likely to report interventions emphasising human rights perspectives and empowerment. There was little robust evidence on the role of CICICE interventions in building preparedness. Evidence of effect was most robust for multi-component interventions for HIV prevention and control. Much of the reporting focused on intermediate outcomes, including measures of health service utilisation. We put forward a series of recommendations to help address evidence shortfalls, including clarifying definitions, organising and stratifying interventions by several parameters and strengthening evaluation methods for CICICE.

Behind the Scenes: Facilitators and Barriers to Developing State Scarce Resource Allocation Plans for the COVID-19 Pandemic

In response to COVID-19, many states revised, developed, or attempted to develop plans to allocate scarce critical care resources in the event that crisis standards of care were triggered. To our knowledge, no prior analysis has assessed this plan development process, including whether plans were successfully adopted. How did states develop or revise scarce resource allocation plans during the COVID-19 pandemic, and what were the barriers and facilitators to their development and adoption at the state level? Plan authors and state leaders completed a semistructured interview February to September 2022. Interview transcripts were qualitatively analyzed for themes related to plan development and adoption according to the principles of grounded theory. Thirty-six participants from 34 states completed an interview, from states distributed across all US regions. Among participants' states with plans that existed prior to 2020 (n= 24), 17 were revised and adopted in response to COVID-19. Six states wrote a plan de novo, with the remaining states failing to develop or adopt a plan. Thirteen states continued to revise their plans in response to disability or aging bias complaints or to respond to evolving needs. Many participants expressed that urgency in the early days of the pandemic prevented an ideal development process. Facilitators of successful plan development and adoption include: coordination or support from the state department of health and existing relationships with key community partners, including aging and disability rights groups and minoritized communities. Barriers include: lack of perceived political will to adopt a plan and development during a public health emergency. To avoid repeating mistakes from the early days of the COVID-19 response, states should develop or revise plans with community engagement and consider maintaining a standing committee with diverse membership and content expertise to periodically review plans and advise state officials on pandemic preparedness.

The Antiviral Activity of Interferon-Induced Transmembrane Proteins and Virus Evasion Strategies.

Interferons (IFNs) are antiviral cytokines that defend against viral infections by inducing the expression of interferon-stimulated genes (ISGs). Interferon-inducible transmembrane proteins (IFITMs) 1, 2, and 3 are crucial ISG products and members of the CD225 protein family. Compelling evidence shows that IFITMs restrict the infection of many unrelated viruses by inhibiting the virus-cell membrane fusion at the virus entry step via the modulation of lipid composition and membrane properties. Meanwhile, viruses can evade IFITMs' restrictions by either directly interacting with IFITMs via viral glycoproteins or by altering the native entry pathway. At the same time, cumulative evidence suggests context-dependent and multifaceted roles of IFITMs in modulating virus infections and cell signaling. Here, we review the diverse antiviral mechanisms of IFITMs, the viral antagonizing strategies, and the regulation of IFITM activity in host cells. The mechanisms behind the antiviral activity of IFITMs could aid the development of broad-spectrum antivirals and enhance preparedness for future pandemics.