Implementation Science to Respond to the COVID-19 Pandemic

Determinants of the implementation of eHealth-based long-term follow-up care for young cancer survivors: a qualitative study

BACKGROUND

eHealth may help closing gaps in the long-term follow-up care of former young age cancer patients. While its introduction to medical aftercare appears promising, it also faces obstacles in the course of its implementation. This study explored what prospective eHealth applications have to achieve and what facilitating and hindering factors are associated with the implementation of them.

METHODS

A qualitative, explorative-descriptive design involving semi-structured interviews was used in this study. General practitioners (GPs) from urban and rural areas as well as former cancer patients were recruited and interviewed. The interview guide focused on expectations of telemedical care services for the patient group of children and adolescents as well as potential facilitating and hindering factors of the implementation of telemedical care services for former cancer patients. Interviews were recorded, transcribed and analyzed on the basis of qualitative content analysis as described by Kuckartz.

RESULTS

Empiric saturation was reached after 25 interviews, respectively. The age of the physicians surveyed at the time of the interviews ranged from 27 to 71 years, with an average of 42 years. The former patients ranged in age from 21 to 43 at the time of participation, with an average age of 34. The age at diagnosis ranged from 3 to 31 years. eHealth services were considered an effective way to maintain continuity of care and improve the health literacy of cancer survivors. Cooperation with health insurance companies and gamification-elements were regarded as beneficial for the introduction of eHealth structures. Poor interface compatibility, insufficient network coverage and lack of digital literacy were valued as potential barriers.

CONCLUSIONS

If properly introduced, eHealth shows the potential to provide stakeholders with tools that increase their self-efficacy and ability to act. As the technology continues to advance, our data provides application-oriented factors for tailored implementation strategies to bring eHealth into the field.

Qualitative comparative analysis of policies implemented by 26 European countries during the 2020 great lockdown

Introduction

During the first wave of the COVID-19 pandemic in Europe, from March 1 to April 15, 2020, significant variations emerged among countries regarding the implementation of lockdown policies. During this period, viewed strictly from an epidemiological perspective, lockdown measures are considered the most effective means of containing a pandemic. However, the adoption of such measures varied, raising questions about whether the reluctance or failure of countries to implement lockdown policies reflected a disregard for epidemiological knowledge or stemmed from an inability to enforce these measures.

Methods

This article employs Qualitative Comparative Analysis (QCA) with 26 European countries as case studies to investigate under what combination of conditions a country would implement lockdown policies.

Results

The QCA results identify three distinct combinations of conditions that lead countries to implement lockdown measures. First, countries with relatively concentrated political power are more likely to implement lockdown policies. Among the 10 countries governed by a majority party or majority coalition within a two-party or moderate multi-party system, seven implemented lockdown policies. Second, in cases of relatively dispersed political power, countries facing state fragility risks are more likely to implement lockdown policies. Among the eight countries that meet both conditions, five implemented lockdown policies. Finally, factors such as political heritage, severity of the pandemic, demographic composition, healthcare access, quality standards, and the ruling party's ideology play a lesser role in the decision to enact lockdown measures.

Discussion

This article offers a novel perspective on the dynamics of party politics and state capacity in the context of decision-making during the COVID-19 pandemic. It contributes to a deeper understanding of the intricate relationship between political systems and public health crisis management, highlighting how various political and governance factors influence the adoption of public health interventions during crises.

The impact of psychological resilience on chronic patients' depression during the dynamic Zero-COVID policy: the mediating role of stigma and the moderating role of sleep quality

OBJECTIVE

Chronic patients are experiencing depression caused by themselves or the surrounding environment, how to cope with the change of mentality and adjust the psychological stress response, especially under the background of the current dynamic Zero-COVID policy in China, is a problem worth further discussion. The researchers constructed a mediating regulation model to test the influence of psychological resilience on depression of chronic patients during dynamic Zero-COVID, as well as the mediating role of stigma and the moderating role of sleep.

METHOD

From October 2021 to February 2022, this study used a multi-stage sampling method and random number table method to collect data in the Shang Cheng District of Hangzhou City, Zhejiang Province. Firstly, the Second Affiliated Hospital of the Zhejiang University School of Medicine, a third-class hospital was randomly selected from the Shang Cheng District. Secondly, three departments were strategically selected from this hospital: endocrinology, dermatology, and traditional Chinese medicine. Thirdly, survey points were set up in each department, and chronic patients were strategically selected for questionnaire surveys. Finally, a face-to-face survey was conducted on 398 chronic patients who met the criteria for inclusion. In addition, chronic medical illness burden was assessed using the Cumulative Illness Rating Scale-Geriatrics (CIRS-G), psychological resilience was measured by the Conner-Davidson Resilience Scale (CD-RISC), stigma was measured by the Stigma Scale for Chronic Illness (SSCI), sleep was measured by the Pittsburgh Sleep Quality Index(PSQI) and depression was estimated by the Patient Health Questionaire-9(PHQ-9). SPSS (version 25.0) and PROCESS (version 4.0) were used for correlation analysis, mediation analysis, and mediated moderation analysis.

RESULTS

Psychological resilience was negatively correlated with depression, stigma, and sleep. Depression was positively correlated with stigma and sleep. Stigma and sleep were positively correlated; Stigma played a mediating role in the relationship between psychological resilience and depression; Sleep moderated the first half of the pathway "psychological resilience [Formula: see text] stigma [Formula: see text] depression".

CONCLUSION

Psychological resilience affected depression directly and indirectly through stigma. At the same time, sleep played a moderating role between psychological resilience and depression. The correlation between psychological resilience and stigma was stronger when levels of sleep levels were higher.

Points of entry dynamics: understanding the cross-border threats for Ebola virus disease and COVID-19 in Ghana using a logic model approach

Background

The influx of people across the national borders of Ghana has been of interest and concern in the public health and national security community in recent times due to the low capacity for the prevention and management of epidemics and other public health risks. Although the international health regulations (IHR) stipulate core public health capacities for designated border facilities such as international airports, seaports, and ground crossings, contextual factors that influence the attainment of effective public health measures and response capabilities remain understudied.

Objective

This study aims to assess the relationship between contextual factors and COVID-19 procurement to help strengthen infrastructure resources for points of entry (PoE) public health surveillance functions, thereby eliminating gaps in the design, implementation, monitoring, and evaluation of pandemic-related interventions in Ghana.

Methods

This study employed a mixed-methods design, where quantitative variables were examined for relationships and effect size interactions using multiple linear regression techniques and the wild bootstrap technique. Country-level data was sourced from multiple publicly available sources using the social-ecological framework, logic model, and IHR capacity monitoring framework. The qualitative portion included triangulation with an expert panel to determine areas of convergence and divergence.

Results

The most general findings were that laboratory capacity and Kotoka International Airport testing center positively predicted COVID-19 procurement, and public health response and airline boarding rule negatively predicted COVID-19 procurement.

Conclusion

Contextual understanding of the COVID-19 pandemic and Ebola epidemic is vital for strengthening PoE mitigation measures and preventing disease importation.

Are the epidemic prevention facilities effective? How cities should choose epidemic prevention facilities: Taking Wuhan as an example

The COVID-19 pandemic highlighted the limitations of urban public health emergency response capabilities. Taking Wuhan as an example, this study used breakpoint regression, kernel density analysis, overlay analysis, and accessibility analysis from Stata and ArcGIS, and divided epidemic prevention facilities into the basic epidemic prevention facilities (hospitals), and the emergency epidemic prevention facilities (mobile cabin hospitals) for further analysis. The results showed that over 70% of the basic epidemic prevention facilities in Wuhan were located in high density population areas. On the contrary, most of the emergency epidemic prevention facilities were located in low density population areas. The local treatment effect of the implementation of the emergency epidemic prevention facility policy is about 1, indicating that there was a significant impact of emergency epidemic prevention facilities on outbreak control, which passed the bandwidth test. What’s more, the analysis of the accessibility of residential points revealed that more than 67.3% of people from the residential points could arrive at the epidemic prevention facilities within 15 min, and only 0.1% of them took more than 20 min to arrive. Therefore, the epidemic prevention facilities can effectively curb the spread of the epidemic, and people from residential areas can quickly get there. This study summarized the spatial characteristics of epidemic prevention facilities in Wuhan and analyzed the importance of them, thus providing a new perspective for future research on upgrading the city’s comprehensive disaster prevention system.

Potential of ATR-FTIR-Chemometrics in Covid-19: Disease Recognition

The COVID-19 pandemic has caused major disturbances to human health and economy on a global scale. Although vaccination campaigns and important advances in treatments have been developed, an early diagnosis is still crucial. While PCR is the golden standard for diagnosing SARS-CoV-2 infection, rapid and low-cost techniques such as ATR-FTIR followed by multivariate analyses, where dimensions are reduced for obtaining valuable information from highly complex data sets, have been investigated. Most dimensionality reduction techniques attempt to discriminate and create new combinations of attributes prior to the classification stage; thus, the user needs to optimize a wealth of parameters before reaching reliable and valid outcomes. In this work, we developed a method for evaluating SARS-CoV-2 infection and COVID-19 disease severity on infrared spectra of sera, based on a rather simple feature selection technique (correlation-based feature subset selection). Dengue infection was also evaluated for assessing whether selectivity toward a different virus was possible with the same algorithm, although independent models were built for both viruses. High sensitivity (94.55%) and high specificity (98.44%) were obtained for assessing SARS-CoV-2 infection with our model; for severe COVID-19 disease classification, sensitivity is 70.97% and specificity is 94.95%; for mild disease classification, sensitivity is 33.33% and specificity is 94.64%; and for dengue infection assessment, sensitivity is 84.27% and specificity is 94.64%.

A Perspective on Implementation Outcomes and Strategies to Promote the Uptake of COVID-19 Vaccines

Recent articles have highlighted the importance of incorporating implementation science concepts into pandemic-related research. However, limited research has been documented to date regarding implementation outcomes that may be unique to COVID-19 vaccinations and how to utilize implementation strategies to address vaccine program-related implementation challenges. To address these gaps, we formed a global COVID-19 implementation workgroup of implementation scientists who met weekly for over a year to review the available literature and learn about ongoing research during the pandemic. We developed a hierarchy to prioritize the applicability of "lessons learned" from the vaccination-related implementation literature. We identified applications of existing implementation outcomes as well as identified additional implementation outcomes. We also mapped implementation strategies to those outcomes. Our efforts provide rationale for the utility of using implementation outcomes in pandemic-related research. Furthermore, we identified three additional implementation outcomes: availability, health equity, and scale-up. Results include a list of COVID-19 relevant implementation strategies mapped to the implementation outcomes.

Deliberation, Dissent, and Distrust: Understanding Distinct Drivers of Coronavirus Disease 2019 Vaccine Hesitancy in the United States

BACKGROUND

Despite the availability of safe and efficacious coronavirus disease 2019 vaccines, a significant proportion of the American public remains unvaccinated and does not appear to be immediately interested in receiving the vaccine.

METHODS

In this study, we analyzed data from the US Census Bureau's Household Pulse Survey, a biweekly cross-sectional survey of US households. We estimated the prevalence of vaccine hesitancy across states and nationally and assessed the predictors of vaccine hesitancy and vaccine rejection. In addition, we examined the underlying reasons for vaccine hesitancy, grouped into thematic categories.

RESULTS

A total of 459 235 participants were surveyed from 6 January to 29 March 2021. While vaccine uptake increased from 7.7% to 47%, vaccine hesitancy rates remained relatively fixed: overall, 10.2% reported that they would probably not get a vaccine and 8.2% that they would definitely not get a vaccine. Income, education, and state political leaning strongly predicted vaccine hesitancy. However, while both female sex and black race were factors predicting hesitancy, among those who were hesitant, these same characteristics predicted vaccine reluctance rather than rejection. Those who expressed reluctance invoked mostly "deliberative" reasons, while those who rejected the vaccine were also likely to invoke reasons of "dissent" or "distrust."

CONCLUSIONS

Vaccine hesitancy comprises a sizable proportion of the population and is large enough to threaten achieving herd immunity. Distinct subgroups of hesitancy have distinctive sociodemographic associations as well as cognitive and affective predilections. Segmented public health solutions are needed to target interventions and optimize vaccine uptake.

Variation in community and ambulance care processes for out-of-hospital cardiac arrest during the COVID-19 pandemic: a systematic review and meta-analysis

Bystander cardiopulmonary resuscitation (BCPR), early defibrillation and timely treatment by emergency medical services (EMS) can double the chance of survival from out-of-hospital sudden cardiac arrest (OHCA). We investigated the effect of the COVID-19 pandemic on the pre-hospital chain of survival. We searched five bibliographical databases for articles that compared prehospital OHCA care processes during and before the COVID-19 pandemic. Random effects meta-analyses were conducted, and meta-regression with mixed-effect models and subgroup analyses were conducted where appropriate. The search yielded 966 articles; 20 articles were included in our analysis. OHCA at home was more common during the pandemic (OR 1.38, 95% CI 1.11–1.71, p = 0.0069). BCPR did not differ during and before the COVID-19 pandemic (OR 0.94, 95% CI 0.80–1.11, p = 0.4631), although bystander defibrillation was significantly lower during the COVID-19 pandemic (OR 0.65, 95% CI 0.48–0.88, p = 0.0107). EMS call-to-arrival time was significantly higher during the COVID-19 pandemic (SMD 0.27, 95% CI 0.13–0.40, p = 0.0006). Resuscitation duration did not differ significantly between pandemic and pre-pandemic timeframes. The COVID-19 pandemic significantly affected prehospital processes for OHCA. These findings may inform future interventions, particularly to consider interventions to increase BCPR and improve the pre-hospital chain of survival.

Impact of the COVID-19 Pandemic on Child and Adolescent Mental Health Policy and Practice Implementation

Background: The impact of the 2019 coronavirus pandemic on the mental health of millions worldwide has been well documented, but its impact on prevention and treatment of mental and behavioral health conditions is less clear. The COVID-19 pandemic also created numerous challenges and opportunities to implement health care policies and programs under conditions that are fundamentally different from what has been considered to be usual care. Methods: We conducted a qualitative study to determine the impact of the COVID-19 pandemic on implementation of evidence-based policy and practice by State Mental Health Authorities (SMHA) for prevention and treatment of mental health problems in children and adolescents. Semi-structured interviews were conducted with 29 SMHA representatives of 21 randomly selected states stratified by coronavirus positivity rate and rate of unmet services need. Data analysis with SMHA stakeholders used procedures embedded in the Rapid Assessment Procedure—Informed Community Ethnography methodology. Results: The need for services increased during the pandemic due primarily to family stress and separation from peers. States reporting an increase in demand had high coronavirus positivity and high unmet services need. The greatest impacts were reduced out-of-home services and increased use of telehealth. Barriers to telehealth services included limited access to internet and technology, family preference for face-to-face services, lack of privacy, difficulty using with young children and youth in need of substance use treatment, finding a Health Insurance Portability and Accountability Act (HIPAA)-compliant platform, training providers and clients, and reimbursement challenges. Policy changes to enable reimbursement, internet access, training, and provider licensing resulted in substantially fewer appointment cancellations or no-shows, greater family engagement, reduction in travel time, increased access for people living in remote locations, and increased provider communication and collaboration. States with high rates of coronavirus positivity and high rates of unmet need were most likely to continue use of telehealth post-pandemic. Despite these challenges, states reported successful implementation of policies designed to facilitate virtual services delivery with likely long-term changes in practice. Conclusions: Policy implementation during the pandemic provided important lessons for planning and preparedness for future public health emergencies. Successful policy implementation requires ongoing collaboration among policy makers and with providers.

Phased Implementation of COVID-19 Vaccination: Rapid Assessment of Policy Adoption, Reach and Effectiveness to Protect the Most Vulnerable in the US

The US and the rest of the world have suffered from the COVID-19 pandemic for over a year. The high transmissibility and severity of this virus have provoked governments to adopt a variety of mitigation strategies. Some of these previous measures, such as social distancing and mask mandates, were effective in reducing the case growth rate yet became economically and administratively difficult to enforce as the pandemic continued. In late December 2020, COVID-19 vaccines were first approved in the US and states began a phased implementation of COVID-19 vaccination. However, there is limited quantitative evidence regarding the effectiveness of the phased COVID-19 vaccination. This study aims to provide a rapid assessment of the adoption, reach, and effectiveness of the phased implementation of COVID-19 vaccination. We utilize an event-study analysis to evaluate the effect of vaccination on the state-level daily COVID-19 case growth rate. Through this analysis, we assert that vaccination was effective in reducing the spread of COVID-19 shortly after the first shots were given. Specifically, the case growth rate declined by 0.124, 0.347, 0.345, 0.464, 0.490, and 0.756 percentage points corresponding to the 1–5, 6–10, 11–15, 16–20, 21–25, and 26 or more day periods after the initial shots. The findings could be insightful for policymakers as they work to optimize vaccine distribution in later phases, and also for the public as the COVID-19 related health risk is a contentious issue.

Ultrarapid On-Site Detection of SARS-CoV-2 Infection Using Simple ATR-FTIR Spectroscopy and an Analysis Algorithm: High Sensitivity and Specificity

There is an urgent need for ultrarapid testing regimens to detect the severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] infections in real-time within seconds to stop its spread. Current testing approaches for this RNA virus focus primarily on diagnosis by RT-qPCR, which is time-consuming, costly, often inaccurate, and impractical for general population rollout due to the need for laboratory processing. The latency until the test result arrives with the patient has led to further virus spread. Furthermore, latest antigen rapid tests still require 15-30 min processing time and are challenging to handle. Despite increased polymerase chain reaction (PCR)-test and antigen-test efforts, the pandemic continues to evolve worldwide. Herein, we developed a superfast, reagent-free, and nondestructive approach of attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy with subsequent chemometric analysis toward the prescreening of virus-infected samples. Contrived saliva samples spiked with inactivated γ-irradiated COVID-19 virus particles at levels down to 1582 copies/mL generated infrared (IR) spectra with a good signal-to-noise ratio. Predominant virus spectral peaks are tentatively associated with nucleic acid bands, including RNA. At low copy numbers, the presence of a virus particle was found to be capable of modifying the IR spectral signature of saliva, again with discriminating wavenumbers primarily associated with RNA. Discrimination was also achievable following ATR-FTIR spectral analysis of swabs immersed in saliva variously spiked with virus. Next, we nested our test system in a clinical setting wherein participants were recruited to provide demographic details, symptoms, parallel RT-qPCR testing, and the acquisition of pharyngeal swabs for ATR-FTIR spectral analysis. Initial categorization of swab samples into negative versus positive COVID-19 infection was based on symptoms and PCR results (n = 111 negatives and 70 positives). Following training and validation (using n = 61 negatives and 20 positives) of a genetic algorithm-linear discriminant analysis (GA-LDA) algorithm, a blind sensitivity of 95% and specificity of 89% was achieved. This prompt approach generates results within 2 min and is applicable in areas with increased people traffic that require sudden test results such as airports, events, or gate controls.