The Interaction of Natural and Vaccine-Induced Immunity with Social Distancing Predicts the Evolution of the COVID-19 Pandemic

Analyzing the use of non-pharmaceutical personal protective measures through self-interest and social optimum for the control of an emerging disease

Non-pharmaceutical personal protective (NPP) measures such as face masks use, and hand and respiratory hygiene can be effective measures for mitigating the spread of aerosol/airborne diseases, such as COVID-19, in the absence of vaccination or treatment. However, the usage of such measures is constrained by their inherent perceived cost and effectiveness for reducing transmission risk. To understand the complex interaction of disease dynamics and individuals decision whether to adopt NPP or not, we incorporate evolutionary game theory into an epidemic model such as COVID-19. To compare how self-interested NPP use differs from social optimum, we also investigated optional control from a central planner's perspective. We use Pontryagin's maximum principle to identify the population-level NPP uptake that minimizes disease incidence by incurring the minimum costs. The evolutionary behavior model shows that NPP uptake increases at lower perceived costs of NPP, higher transmission risk, shorter duration of NPP use, higher effectiveness of NPP, and shorter duration of disease-induced immunity. Though social optimum NPP usage is generally more effective in reducing disease incidence than self-interested usage, our analysis identifies conditions under which both strategies get closer. Our model provides new insights for public health in mitigating a disease outbreak through NPP.

Modeling the health impact of increasing vaccine coverage and nonpharmaceutical interventions against coronavirus disease 2019 in Ghana

Seroprevalence studies assessing community exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Ghana concluded that population-level immunity remained low as of February 2021. Thus, it is important to demonstrate how increasing vaccine coverage reduces the economic and public health impacts associated with SARS-CoV-2 transmission. To that end, this study used a Susceptible-Exposed-Presymptomatic-Symptomatic-Asymptomatic-Recovered-Dead-Vaccinated compartmental model to simulate coronavirus disease 2019 (COVID-19) transmission and the role of public health interventions in Ghana. The impact of increasing vaccination rates and decline in transmission rates due to nonpharmaceutical interventions (NPIs) on cumulative infections and deaths averted was explored under different scenarios. Latin hypercube sampling-partial rank correlation coefficient (LHS-PRCC) was used to investigate the uncertainty and sensitivity of the outcomes to the parameters. Simulation results suggest that increasing the vaccination rate to achieve 50% coverage was associated with almost 60,000 deaths and 25 million infections averted. In comparison, a 50% decrease in the transmission coefficient was associated with the prevention of about 150,000 deaths and 50 million infections. The LHS-PRCC results indicated that in the context of vaccination rate, cumulative infections and deaths averted were most sensitive to vaccination rate, waning immunity rates from vaccination, and waning immunity from natural infection. This study's findings illustrate the impact of increasing vaccination coverage and/or reducing the transmission rate by NPI adherence in the prevention of COVID-19 infections and deaths in Ghana.

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review

BACKGROUND

The interaction between modelers and policymakers is becoming more common due to the increase in computing speed seen in recent decades. The recent pandemic caused by the SARS-CoV-2 virus was no exception. Thus, this study aims to identify and assess epidemiological mathematical models of SARS-CoV-2 applied to real-world data, including immunization for coronavirus 2019 (COVID-19).

METHODOLOGY

PubMed, JSTOR, medRxiv, LILACS, EconLit, and other databases were searched for studies employing epidemiological mathematical models of SARS-CoV-2 applied to real-world data. We summarized the information qualitatively, and each article included was assessed for bias risk using the Joanna Briggs Institute (JBI) and PROBAST checklist tool. The PROSPERO registration number is CRD42022344542.

FINDINGS

In total, 5646 articles were retrieved, of which 411 were included. Most of the information was published in 2021. The countries with the highest number of studies were the United States, Canada, China, and the United Kingdom; no studies were found in low-income countries. The SEIR model (susceptible, exposed, infectious, and recovered) was the most frequently used approach, followed by agent-based modeling. Moreover, the most commonly used software were R, Matlab, and Python, with the most recurring health outcomes being death and recovery. According to the JBI assessment, 61.4% of articles were considered to have a low risk of bias.

INTERPRETATION

The utilization of mathematical models increased following the onset of the SARS-CoV-2 pandemic. Stakeholders have begun to incorporate these analytical tools more extensively into public policy, enabling the construction of various scenarios for public health. This contribution adds value to informed decision-making. Therefore, understanding their advancements, strengths, and limitations is essential.

Hydroxychloroquine for Non-Hospitalized COVID-19 Patients: A Systematic Review and Meta-Analysis of Randomized Clinical Trials

BACKGROUND

Previous systematic reviews have identified no benefit of hydroxychloroquine and chloroquine in non-hospitalized COVID-19 patients. After publication of these reviews, the results of COPE, the largest randomized trial conducted to date, became available.

OBJECTIVES

To conduct a systematic review and meta-analyses of randomized clinical trials (RCTs) to synthesize the evidence on the efficacy and safety of hydroxychloroquine and chloroquine for non-hospitalized COVID-19 patients compared to placebo or standard of care.

METHODS

Searches were conducted in PubMed, Embase, The Cochrane Library, and ClinicalTrials.gov complemented by manual search. Pairwise meta-analyses, risk of bias, and evidence certainty assessments were conducted, including optimal information size analysis (OIS). A level of significance of 0.05 was adopted in the meta-analysis. PROSPERO: CRD42021265427.

RESULTS

Eight RCTs with 3,219 participants were included. COVID-19 hospitalization and any adverse events rates were not significantly different between hydroxychloroquine (5.6% and 35.1%) and control (7.4% and 20.4%) (risk ratio, RR, 0.77, 95% confidence interval, CI, 0.57-1.04, I2: 0%; RR 1.78, 95%-CI 0.90; 3.52, I2: 93%, respectively). The OIS (7,880) was not reached for COVID-19 hospitalization, independently of the simulation for anticipated event rate and RR reduction estimate.

CONCLUSION

Evidence of very low certainty showed lack of benefit with hydroxychloroquine in preventing COVID-19 hospitalizations. Despite being the systematic review with the largest number of participants included, the OIS, considering pre-vaccination response to infection, has not yet been reached.

Age-Stratified Model to Assess Health Outcomes of COVID-19 Vaccination Strategies, Ghana

We assessed the effect of various COVID-19 vaccination strategies on health outcomes in Ghana by using an age-stratified compartmental model. We stratified the population into 3 age groups: <25 years, 25-64 years, and ≥65 years. We explored 5 vaccination optimization scenarios using 2 contact matrices, assuming that 1 million persons could be vaccinated in either 3 or 6 months. We assessed these vaccine optimization strategies for the initial strain, followed by a sensitivity analysis for the Delta variant. We found that vaccinating persons <25 years of age was associated with the lowest cumulative infections for the main matrix, for both the initial strain and the Delta variant. Prioritizing the elderly (≥65 years of age) was associated with the lowest cumulative deaths for both strains in all scenarios. The consensus between the findings of both contact matrices depended on the vaccine rollout period and the objective of the vaccination program.

Neutralizing antibodies against SARS-CoV-2 in Brazilian pregnant women vaccinated with one or two doses of BNT162b2 mRNA vaccine (Pfizer/WyethTM)

Pregnant women have an increased risk of developing severe coronavirus disease. In Brazil, the number of hospitalizations and adverse outcomes, including death caused by COVID-19, in women during the pregnancy-puerperal cycle was high in the first pandemic year. Doubts regarding vaccines' efficacy and safety for the mother and fetus delayed vaccination. This study evaluated the generation of IgG titers and neutralizing antibodies to the BNT162b2 mRNA vaccine in 209 healthy pregnant women. For this, were used the QuantiVac ELISA (IgG) and SARS-CoV-2 NeutraLISA kits (EUROIMMUN, Lübeck, SH) following the manufacturer's recommendations. One dose vaccine produced anti-SARS-CoV-2 IgG in 85% (81/95), and two produced in 95% (76/80) women. Among unvaccinated women, four of 34 (12%) showed protection. The first dose of the BNT162b2 vaccine protected 69% of the women with neutralizing antibodies (median of %IH = 97). In the second dose, protection occurred in 94% of the pregnant women (median of IH% = 97). This study showed no differences in IgG antibody titers between one- and two-dose of the BNT162b2 mRNA vaccine groups, boosting with the second dose increased the number of women who produced specific IgG and neutralizing antibodies, raising by 114-folds the chance of producing the SARS-CoV-2 neutralizing antibodies compared to the unvaccinated pregnant woman, which may contribute to reduce the chance of severe COVID-19.

Community structured model for vaccine strategies to control COVID19 spread: A mathematical study

Initial efforts to mitigate the COVID-19 pandemic have relied heavily on non-pharmaceutical interventions (NPIs), including physical distancing, hand hygiene, and mask-wearing. However, an effective vaccine is essential to containing the spread of the virus. We developed a compartmental model to examine different vaccine strategies for controlling the spread of COVID-19. Our framework accounts for testing rates, test-turnaround times, and vaccination waning immunity. Using reported case data from the city of Toronto, Canada between Mar-Dec, 2020 we defined epidemic phases of infection using contact rates as well as the probability of transmission upon contact. We investigated the impact of vaccine distribution by comparing different permutations of waning immunity, vaccine coverage and efficacy throughout various stages of NPI's relaxation in terms of cases and deaths. The basic reproduction number is also studied. We observed that widespread vaccine coverage substantially reduced the number of cases and deaths. Under phases with high transmission, an early or late reopening will result in new resurgence of the infection, even with the highest coverage. On the other hand, under phases with lower transmission, 60% of coverage is enough to prevent new infections. Our analysis of R0 showed that the basic reproduction number is reduced by decreasing the tests turnaround time and transmission in the household. While we found that household transmission can decrease following the introduction of a vaccine, public health efforts to reduce test turnaround times remain important for virus containment.

Vaccinating Children against COVID-19: Commentary and Mathematical Modeling

With the recent licensure of mRNA vaccines against COVID-19 in the 5- to 11-year-old age group, the public health impact of a childhood immunization campaign is of interest. Using a mathematical epidemiological model, we project that childhood vaccination carries minimal risk and yields modest public health benefits. These include large relative reductions in child morbidity and mortality, although the absolute reduction is small because these events are rare. Furthermore, the model predicts "altruistic" absolute reductions in adult cases, hospitalizations, and mortality. However, vaccinating children to benefit adults should be considered from an ethical as well as a public health perspective. From a global health perspective, an additional ethical consideration is the justice of giving priority to children in high-income settings at low risk of severe disease while vaccines have not been made available to vulnerable adults in low-income settings. IMPORTANCE Countries have recently begun implementation of childhood vaccination against SARS-CoV-2 with the Pfizer/BioNTech mRNA vaccine in children 5 to 11 years of age. Because SARS-CoV-2 disease severity is remarkably age dependent, vaccinating children may have modest public health benefits, relative to the unequivocal benefit of vaccinating vulnerable older adults. Furthermore, vaccinating children to "altruistically" increase herd immunity should be considered from an ethical as well as a public health perspective. An additional question is related to global social justice: should priority be given to vaccinating children in high-income settings while older adult populations in low-resource settings have limited access to vaccine? To address the risks and benefits of childhood vaccination, we provide a balanced commentary, supported by a mathematical epidemiological model, using Australia and Alberta, Canada, as case studies. We give highlights of the modeling findings in the commentary and include details in the supplemental materials for interested readers.

Antibody Response to SARS-CoV-2 in Relation to the Contributing Factors in COVID-19 Patients

Human health has always been challenged by variety of viral infections, but severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has surpassed all previous viral diseases and emerged as a major health challenge around the globe. Real-time polymerase chain reaction (PCR) is the gold standard for the diagnosis of SARS-CoV-2 and serological assay provides a compliment to diagnosis after second week of infection. The aim of the study is the characterization of antibody response to SARS-CoV-2 in the blood sample of diagnosed coronavirus disease 2019 (COVID-19) patients, and its potential association with factors such as age, gender, time, and symptoms. Serum from 248 confirmed SARS-CoV-2 patients was investigated for antibodies. Elecsys anti-SARS chemiluminescent immune assay was performed for the detection of nucleocapsid-specific antibodies. Association of antibody response with gender, age, and time after onset of symptoms was analyzed. Among 248 PCR positive SARS-CoV-2 patients, 214 (86.3%) have virus-specific antibody signals. Antibodies positivity rate was higher in male patient patients as compared with female patients (90.8% vs. 79.2%, p = 0.009). Patients aged 30-40 years had the highest antibody positivity rate as compared with other groups (89.10%, p = 0.04). Patients age group >60 years had a lower positivity rate (75%, p = 0.04). The increasing trend in the antibodies detection with time was observed, maximum positive antibodies response rate observed at 8 weeks. Patients were categorized on the basis of clinical symptoms into asymptomatic, mild, and moderate; 17.7% were asymptomatic, 60.5% showed mild symptoms, and 21.8% showed moderate symptoms of the disease. Males were seen to be more asymptomatic as compared with females (i.e., 59.1% to 40.9%). The serological test for SARS-CoV-2 has a high sensitivity at >2 weeks after the positive PCR result or onset of illness. In addition, the serological response differs among patients based on gender, age, as well as time between the onset of symptoms or PCR confirmation and sample collection for the study of antibody response.

Modelling COVID-19 dynamics and potential for herd immunity by vaccination in Austria, Luxembourg and Sweden

Against the COVID-19 pandemic, non-pharmaceutical interventions have been widely applied and vaccinations have taken off. The upcoming question is how the interplay between vaccinations and social measures will shape infections and hospitalizations. Hence, we extend the Susceptible-Exposed-Infectious-Removed (SEIR) model including these elements. We calibrate it to data of Luxembourg, Austria and Sweden until 15 December 2020. Sweden results having the highest fraction of undetected, Luxembourg of infected and all three being far from herd immunity in December. We quantify the level of social interaction, showing that a level around 1/3 of before the pandemic was still required in December to keep the effective reproduction number Refft below 1, for all three countries. Aiming to vaccinate the whole population within 1 year at constant rate would require on average 1,700 fully vaccinated people/day in Luxembourg, 24,000 in Austria and 28,000 in Sweden, and could lead to herd immunity only by mid summer. Herd immunity might not be reached in 2021 if too slow vaccines rollout speeds are employed. The model thus estimates which vaccination rates are too low to allow reaching herd immunity in 2021, depending on social interactions. Vaccination will considerably, but not immediately, help to curb the infection; thus limiting social interactions remains crucial for the months to come.

Structure of epidemic models: toward further applications in economics

In this paper, we review the structure of various epidemic models in mathematical epidemiology for the future applications in economics. The heterogeneity of population and the generalization of nonlinear terms play important roles in making more elaborate and realistic models. The basic, effective, control and type reproduction numbers have been used to estimate the intensity of epidemic, to evaluate the effectiveness of interventions and to design appropriate interventions. The advanced epidemic models includes the age structure, seasonality, spatial diffusion, mutation and reinfection, and the theory of reproduction numbers has been generalized to them. In particular, the existence of sustained periodic solutions has attracted much interest because they can explain the recurrent waves of epidemic. Although the theory of epidemic models has been developed in decades and the development has been accelerated through COVID-19, it is still difficult to completely answer the uncertainty problem of epidemic models. We would have to mind that there is no single model that can solve all questions and build a scientific attitude to comprehensively understand the results obtained by various researchers from different backgrounds.

Public awareness about coronavirus vaccine, vaccine acceptance, and hesitancy

Measurement of the population's general knowledge of the coronavirus vaccine is very important to improve public acceptance and decrease vaccine hesitancy in confronting the disease. This study aimed to evaluate the knowledge, attitude, and practices of the participants towards the coronavirus vaccine. Data were collected using an online survey, in the form of a structured questionnaire, conducted during April-May 2021 in Egypt, and subjects from all over Egypt participated. The questionnaire was divided into three parts to assess the knowledge and attitude regarding coronavirus. The first part was to assess participants' experience about coronavirus infection (eight items), the second was to assess the health beliefs about coronavirus and vaccine (16 items) and the third was to assess general knowledge, attitude, and practices of the participants towards vaccine (28 items). A total of 871 (465 females) participants participated, 81% of them were still committed to the precautionary measures for protection. Eighty-eight percent of them accepted to take the vaccine. Eighty-three percent of the participants answered that they will encourage family, friends, and colleagues to get the vaccine. Ninety-four percent knew that the coronavirus vaccine provides immunity against infection for a period of 6-12 months. 91.9% believed that the current infection with coronavirus is one of the main contraindications to vaccination. Eighty-nine percent believed that both pregnant women and chronic disease patients can get vaccinated and also that there is no specific age for a specific type of vaccination. Ninety-four percent of them knew that subjects taking immunosuppressive drugs should be prescribed Sinopharm, not AstraZeneca vaccine. The median score of this survey was 20/22 regarding knowledge about the coronavirus vaccine. Overall, the study participants had good knowledge about the coronavirus vaccine and accepted to take the vaccine, which indicates the highly commendable efforts to confront the coronavirus.

INFECTION-ACQUIRED VERSUS VACCINE-INDUCED IMMUNITY AGAINST COVID-19

The course of COVID-19 depends on a dynamic interplay between SARS-CoV-2 and the host's immune system. Although it is an emerging global health issue, little is known about the specificity, safety, and duration of the immunity elicited by the virus. This hypothesis article explores the benefits of infection-acquired and vaccine-induced immunity against COVID-19, suggesting that the latter outweighs the former. Comparative studies are proposed to explain and reveal all aspects of the immune responses. Although vaccine development relies on studies of naturally acquired immune responses, there are still no comparative analyses of the natural and vaccine immunity against SARS-CoV-2. Moreover, there are scarce reports on the characteristics of both types of responses. The scientific facts about the virulence of SARS-CoV-2 affecting the immune system are of great importance for proposed comparative analyses. Various immunological methods can be employed to elucidate infection-acquired and vaccine-induced immunity against SARS-CoV-2. The safe vaccination of subjects with and without COVID-19 history may disrupt the virus spreading and end the pandemic.