Leveraging lessons from the COVID-19 pandemic to strengthen low-income and middle-income country preparedness for future global health threats

Risk factors related to the SARS-CoV-2 vaccine additional doses hesitancy among pregnant and non-pregnant people of reproductive age and partners: A Brazilian cross-sectional study

OBJECTIVE

The aim of this study was to assess the predictors of acceptance and hesitancy of additional doses of any SARS-CoV-2 (COVID-19) vaccine among pregnant or recently pregnant and non-pregnant people of reproductive age and partners in Brazil.

METHODS

We conducted an online cross-sectional study from June 2022 to April 2023 and invited women and partners between 18 and 49 years old to participate. We employed a snowball strategy to reach all potential eligible participants. Our primary outcome was the acceptance rate of the COVID-19 booster vaccine. We estimated the frequency and percentage for the three groups and compared categorical variables using the Chi-square test. Moreover, bivariate, backward stepwise regression, and subgroup analyses were performed to evaluate risk factors and predictors of COVID-19 vaccine booster hesitancy. We reported the effect size as OR with a 95% CI.

RESULTS

We included 1487 participants, and among them, 334 (22.5%) were pregnant or recently pregnant people, 905 (60.8%) were non-pregnant people, and 247 (16.6%) were male partners. Pregnant and recently pregnant people showed greater hesitancy for the COVID-19 vaccine booster than non-pregnant people (28% vs 15%, P < 0.001) and male partners (28% vs 16%, P < 0.001). Non-pregnant women accepted the COVID-19 vaccine more often than pregnant or recently pregnant people (OR 1.75; 95% CI: 1.13-2.70). The associated factors to the reduced COVID-19 vaccine booster acceptance were family income between US$ 566-945.00 (54%), evangelic religion (65%), concern about vaccine safety (80%) and perceived common vaccine importance (93%).

CONCLUSION

Pregnant people were more hesitant than non-pregnant people to accept the COVID-19 booster vaccine. Family income, religious beliefs, vaccine safety concerns, and perceived common vaccine importance were significant barriers to accepting COVID-19 booster vaccines. The impact of these factors was more evident among pregnant or recently pregnant people, emphasizing the harmful effect of misinformation among this vulnerable population.

Healthcare professionals' understanding and perception of drug-related issues linked to off-label pharmacological medications used for COVID-19

BACKGROUND

To evaluate the opinions of healthcare workers regarding drug therapy problems linked to anti-infective medicines used for the treatment of COVID-19 infection in Pakistan.

RESEARCH METHODOLOGY

This cross-sectional study was conducted from January to October 2022 using a self-administered questionnaire developed by the authors, having three sections: demographics, knowledge, and perception. The study was validated by research experts and pilot-tested on 30 subjects. The study included medical doctors, nurses, pharmacists from Punjab's government and private medical institutes.

RESULTS

In this study, 382 of 400 participants replied. The mean knowledge score was 9.52 (SD 2.97), showing that participants had adequate knowledge of COVID-19 pharmacological interventions. The knowledge scores were significantly higher of those who treated COVID-19 patients and were from Lahore. Many doctors considered that elderly patients and those with blood disorders were at greater risk of experiencing drug-related problems. Most pharmacists support electronic prescription systems. Many doctors thought the lack of unified treatment guidelines, multiple prescribers, and self-medication were key obstacles in managing COVID-19 patients.

CONCLUSION

Most respondents had adequate knowledge. Older patients with comorbidities are at risk of adverse effects. Self-medication, polypharmacy, and multiple prescriptions can lead to misdiagnosis and complications. Electric prescriptions, team effort, and training programs can decrease these issues.

Variability of the treated biomedical waste disposal behaviours during the COVID lockdowns

Literature review suggests that studies on biomedical waste generation and disposal behaviors in North America are limited. Given the infectious nature of the materials, effective biomedical waste management is vital to the public health and safety of the residents. This study explicitly examines seasonal variations of treated biomedical waste (TBMW) disposal rates in the City of Regina, Canada, from 2013 to 2022. Immediately before the onset of COVID-19, the City exhibited a steady pattern of TBMW disposal rate at about 6.6 kg∙capita-1∙year-1. However, the COVID-19 pandemic and its associated lockdowns brought about an abrupt and persistent decline in TBMW disposal rates. Inconsistent fluctuations in both magnitude and variability of the monthly TBMW load weights were also observed. The TBMW load weight became particularly variable in 2020, with an interquartile range 4 times higher than 2019. The average TBMW load weight was also the lowest (5.1 tonnes∙month-1∙truckload-1) in 2020, possibly due to an overall decline in non-COVID-19 medical emergencies, cancellation of elective surgeries, and availability of telehealth options to residents. In general, the TBMW disposal rates peaked during the summer and fall seasons. The day-to-day TBMW disposal contribution patterns between the pre-pandemic and post-pandemic are similar, with 97.5% of total TBMW being disposed of on fixed days. Results from this Canadian case study indicate that there were observable temporal changes in TBMW disposal behaviors during and after the COVID-19 lockdowns.

Next-generation treatments: Immunotherapy and advanced therapies for COVID-19

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in 2019 following prior outbreaks of coronaviruses like SARS and MERS in recent decades, underscoring their high potential of infectivity in humans. Insights from previous outbreaks of SARS and MERS have played a significant role in developing effective strategies to mitigate the global impact of SARS-CoV-2. As of January 7, 2024, there have been 774,075,242 confirmed cases of COVID-19 worldwide. To date, 13.59 billion vaccine doses have been administered, and there have been 7,012,986 documented fatalities (https://www.who.int/) Despite significant progress in addressing the COVID-19 pandemic, the rapid evolution of SARS-CoV-2 challenges human defenses, presenting ongoing global challenges. The emergence of new SARS-CoV-2 lineages, shaped by mutation and recombination processes, has led to successive waves of infections. This scenario reveals the need for next-generation vaccines as a crucial requirement for ensuring ongoing protection against SARS-CoV-2. This demand calls for formulations that trigger a robust adaptive immune response without leading the acute inflammation linked with the infection. Key mutations detected in the Spike protein, a critical target for neutralizing antibodies and vaccine design -specifically within the Receptor Binding Domain region of Omicron variant lineages (B.1.1.529), currently dominant worldwide, have intensified concerns due to their association with immunity evasion from prior vaccinations and infections. As the world deals with this evolving threat, the narrative extends to the realm of emerging variants, each displaying new mutations with implications that remain largely misunderstood. Notably, the JN.1 Omicron lineage is gaining global prevalence, and early findings suggest it stands among the immune-evading variants, a characteristic attributed to its mutation L455S. Moreover, the detrimental consequences of the novel emergence of SARS-CoV-2 lineages bear a particularly critical impact on immunocompromised individuals and older adults. Immunocompromised individuals face challenges such as suboptimal responses to COVID-19 vaccines, rendering them more susceptible to severe disease. Similarly, older adults have an increased risk of severe disease and the presence of comorbid conditions, find themselves at a heightened vulnerability to develop COVID-19 disease. Thus, recognizing these intricate factors is crucial for effectively tailoring public health strategies to protect these vulnerable populations. In this context, this review aims to describe, analyze, and discuss the current progress of the next-generation treatments encompassing immunotherapeutic approaches and advanced therapies emerging as complements that will offer solutions to counter the disadvantages of the existing options. Preliminary outcomes show that these strategies target the virus and address the immunomodulatory responses associated with COVID-19. Furthermore, the capacity to promote tissue repair has been demonstrated, which can be particularly noteworthy for immunocompromised individuals who stand as vulnerable actors in the global landscape of coronavirus infections. The emerging next-generation treatments possess broader potential, offering protection against a wide range of variants and enhancing the ability to counter the impact of the constant evolution of the virus. Furthermore, advanced therapies are projected as potential treatment alternatives for managing Chronic Post-COVID-19 syndromeand addressing its associated long-term complications.

Human resource implications of expanding latent tuberculosis patient care activities

Introduction

The World Health Organization (WHO) declared increasing services for latent tuberculosis infection (LTBI) a priority to eliminate tuberculosis (TB) by 2035. Yet, there is little information about thehuman resource needs required to implement LTBI treatment scale-up. Our study aimed to estimate the change in healthcare workers (HCW) time spent on different patient care activities, following an intervention to strengthen LTBI services.

Methods

We conducted a time and motion (TAM) study, observing HCW throughout a typical workday before and after the intervention (Evaluation and Strengthening phases, respectively) at 24 health facilities in five countries. The precise time spent on pre-specified categories of work activities was recorded. Time spent on direct patient care was subcategorized as relating to one of three conditions: LTBI, active or suspected TB, and non-TB (i.e., patients with any other medical condition). A linear mixed model (LMM) was fit to estimate the change in HCW time following the intervention.

Results

A total of 140 and 143 HCW participated in the TAMs during the Evaluation and Strengthening phases, respectively. Results from intervention facilities showed an increase of 9% (95% CI: 3%, 15%) in the proportion of HCW time spent on LTBI-related services, but with a corresponding change of -11% (95% CI: -21%, -1%) on active TB services. There was no change in the proportion of time spent on LTBI care in control facilities; this remained low in both phases of the study.

Discussion

Our findings suggest that additional HCW personnel will be required for expansion of LTBI services to ensure that this expansion does not reduce the time available for care of active TB patients.

Development and Validation of a Robust and Interpretable Early Triaging Support System for Patients Hospitalized With COVID-19: Predictive Algorithm Modeling and Interpretation Study

BACKGROUND

Robust and accurate prediction of severity for patients with COVID-19 is crucial for patient triaging decisions. Many proposed models were prone to either high bias risk or low-to-moderate discrimination. Some also suffered from a lack of clinical interpretability and were developed based on early pandemic period data. Hence, there has been a compelling need for advancements in prediction models for better clinical applicability.

OBJECTIVE

The primary objective of this study was to develop and validate a machine learning-based Robust and Interpretable Early Triaging Support (RIETS) system that predicts severity progression (involving any of the following events: intensive care unit admission, in-hospital death, mechanical ventilation required, or extracorporeal membrane oxygenation required) within 15 days upon hospitalization based on routinely available clinical and laboratory biomarkers.

METHODS

We included data from 5945 hospitalized patients with COVID-19 from 19 hospitals in South Korea collected between January 2020 and August 2022. For model development and external validation, the whole data set was partitioned into 2 independent cohorts by stratified random cluster sampling according to hospital type (general and tertiary care) and geographical location (metropolitan and nonmetropolitan). Machine learning models were trained and internally validated through a cross-validation technique on the development cohort. They were externally validated using a bootstrapped sampling technique on the external validation cohort. The best-performing model was selected primarily based on the area under the receiver operating characteristic curve (AUROC), and its robustness was evaluated using bias risk assessment. For model interpretability, we used Shapley and patient clustering methods.

RESULTS

Our final model, RIETS, was developed based on a deep neural network of 11 clinical and laboratory biomarkers that are readily available within the first day of hospitalization. The features predictive of severity included lactate dehydrogenase, age, absolute lymphocyte count, dyspnea, respiratory rate, diabetes mellitus, c-reactive protein, absolute neutrophil count, platelet count, white blood cell count, and saturation of peripheral oxygen. RIETS demonstrated excellent discrimination (AUROC=0.937; 95% CI 0.935-0.938) with high calibration (integrated calibration index=0.041), satisfied all the criteria of low bias risk in a risk assessment tool, and provided detailed interpretations of model parameters and patient clusters. In addition, RIETS showed potential for transportability across variant periods with its sustainable prediction on Omicron cases (AUROC=0.903, 95% CI 0.897-0.910).

CONCLUSIONS

RIETS was developed and validated to assist early triaging by promptly predicting the severity of hospitalized patients with COVID-19. Its high performance with low bias risk ensures considerably reliable prediction. The use of a nationwide multicenter cohort in the model development and validation implicates generalizability. The use of routinely collected features may enable wide adaptability. Interpretations of model parameters and patients can promote clinical applicability. Together, we anticipate that RIETS will facilitate the patient triaging workflow and efficient resource allocation when incorporated into a routine clinical practice.

Vaccine development against tuberculosis before and after Covid-19

Coronavirus disease (Covid-19) has not only shaped awareness of the impact of infectious diseases on global health. It has also provided instructive lessons for better prevention strategies against new and current infectious diseases of major importance. Tuberculosis (TB) is a major current health threat caused by Mycobacterium tuberculosis (Mtb) which has claimed more lives than any other pathogen over the last few centuries. Hence, better intervention measures, notably novel vaccines, are urgently needed to accomplish the goal of the World Health Organization to end TB by 2030. This article describes how the research and development of TB vaccines can benefit from recent developments in the Covid-19 vaccine pipeline from research to clinical development and outlines how the field of TB research can pursue its own approaches. It begins with a brief discussion of major vaccine platforms in general terms followed by a short description of the most widely applied Covid-19 vaccines. Next, different vaccination regimes and particular hurdles for TB vaccine research and development are described. This specifically considers the complex immune mechanisms underlying protection and pathology in TB which involve innate as well as acquired immune mechanisms and strongly depend on fine tuning the response. A brief description of the TB vaccine candidates that have entered clinical trials follows. Finally, it discusses how experiences from Covid-19 vaccine research, development, and rollout can and have been applied to the TB vaccine pipeline, emphasizing similarities and dissimilarities.

COVID-19 vaccination acceptance, safety and side-effects in European patients with severe asthma

Background

Vaccination is vital for achieving population immunity to severe acute respiratory syndrome coronavirus 2, but vaccination hesitancy presents a threat to achieving widespread immunity. Vaccine acceptance in chronic potentially immunosuppressed patients is largely unclear, especially in patients with asthma. The aim of this study was to investigate the vaccination experience in people with severe asthma.

Methods

Questionnaires about vaccination beliefs (including the Vaccination Attitudes Examination (VAX) scale, a measure of vaccination hesitancy-related beliefs), vaccination side-effects, asthma control and overall safety perceptions following coronavirus disease 2019 (COVID-19) vaccination were sent to patients with severe asthma in 12 European countries between May and June 2021.

Results

660 participants returned completed questionnaires (87.4% response rate). Of these, 88% stated that they had been, or intended to be, vaccinated, 9.5% were undecided/hesitant and 3% had refused vaccination. Patients who hesitated or refused vaccination had more negative beliefs towards vaccination. Most patients reported mild (48.2%) or no side-effects (43.8%). Patients reporting severe side-effects (5.7%) had more negative beliefs. Most patients (88.8%) reported no change in asthma symptoms after vaccination, while 2.4% reported an improvement, 5.3% a slight deterioration and 1.2% a considerable deterioration. Almost all vaccinated (98%) patients would recommend vaccination to other severe asthma patients.

Conclusions

Uptake of vaccination in patients with severe asthma in Europe was high, with a small minority refusing vaccination. Beliefs predicted vaccination behaviour and side-effects. Vaccination had little impact on asthma control. Our findings in people with severe asthma support the broad message that COVID-19 vaccination is safe and well tolerated.

Lessons learned from behaviors of the employees in Iranian banks during the Covid-19 pandemic crisis: A phenomenological study

The aim of this research is to analyze the experiences of employees during the Covid-19 pandemic cri-sis and conceptualize the lessons learned to deal with similar crises in the future. To achieve this, a qualitative approach with a phenomenological strategy was conducted through semi-structured, in-depth interviews with 16 front-line employees of Bank Melli, the largest state bank in Iran. The study found that employee behavior plays a critical role in crisis management, with functional behaviors such as preventive measures, stress management, and sharing valid information being essential. Dysfunctional behaviors such as resistance to change and inconsistent behaviors were also identified. The prevention of infection and stress management were identified as key behaviors to cope with the crisis, while media literacy and acceptance of change were crucial for correct information analysis and crisis management. Overall, the study highlights the challenges faced by employees during the Covid-19 crisis and provides valuable lessons from a behavioral perspective for managers in the banking industry to manage disruptions caused by current and future pandemics. The study emphasizes the importance of learning from the lessons of the Covid-19 crisis to reduce negative effects on physical and mental health.