Seroprevalence of anti-SARS-CoV-2 antibodies among staff at primary healthcare institutions in Prishtina

Background Many studies examined the spread of SARS-CoV-2 within populations using seroprevalence. Healthcare workers are a high-risk population due to patient contact, and studies are needed to examine seroprevalence of SARS-CoV-2 antibodies among healthcare workers. Our study investigates the seroprevalence of anti-SARS-CoV-2 antibodies among staff at primary healthcare institutions in Prishtina, and factors associated with seroprevalence. Methods We carried out a cross-sectional survey including SARS-CoV-2 serological testing and questionnaires with primary healthcare workers from primary healthcare facilities in the Prishtina, the capital city of Kosovo. We calculated prevalence of anti-SARS-CoV-2 antibodies, and of self-reported positive PCR test among primary healthcare workers, as well as crude and adjusted ORs for explanatory factors. Results Eighty-three of the healthcare workers (17.47%) tested positive for SARS-CoV-2 antibodies IgG or IgM, while 231 (48.63%) either had antibodies or a previous positive PCR test. Odds of seropositivity were affected by male gender (OR 2.08, 95% CI 1.20, 3.61), and infected family members (OR 3.61, 95% CI 2.25, 5.79) of healthcare workers. Higher education, being part of larger families and having infected family members gave higher odds of positive PCR test and seropositivity. Other healthcare workers had lower odds of positive PCR test and seropositivity than physicians. Conclusion Over 17% of healthcare workers were seropositive for SARS-CoV-2 antibodies and close to half of them were either seropositive or PCR self-reported positive test. Several factors are associated with decreased and increased odds for such outcomes. These findings should be explored further and addressed to Kosovo policy makers, and assist them to intensify vaccination efforts, and maintain control measures until we achieve herd immunity.

Seroprevalence of IgG antibodies against diphtheria antitoxin among migrant workers in Singapore, 2016–2019

Background Since the last local case of diphtheria in 1992, there had not been any case in Singapore until an autochthonous case was reported in 2017. This fatal diphtheria case of a migrant worker raised concerns about the potential re-emergence of locally transmitted toxigenic diphtheria in Singapore. We conducted a seroprevalence study to assess the immunity levels to diphtheria among migrant workers in Singapore. Methods Residual sera from migrant workers who hailed from Bangladesh, China, India, Indonesia, Malaysia, Myanmar and the Philippines were tested for anti-diphtheria toxoid immunoglobulin G (IgG) antibodies. These migrant workers previously participated in a survey between 2016 and 2019 and had provided blood samples as part of the survey procedure. Results A total of 2176 migrant workers were included in the study. Their overall mean age was 27.1 years (standard deviation 5.0), range was 20–43 years. The proportion having at least basic protection against diphtheria (antitoxin titres ≥ 0.01 IU/ml) ranged from 77.9% (95% confidence interval [CI] 72.8 – 82.3%) among migrant workers from Bangladesh to 96.7% (95% CI 92.5 – 98.6%) in those hailing from Malaysia. The proportion showing full protection (antitoxin titres ≥ 0.10 IU/ml) ranged from 10.1% (95% CI 6.5 – 15.4%) in Chinese workers to 23.0% (95% CI 17.1 – 30.3%) in Malaysian workers. There were no significant differences in the proportion with at least basic protection across birth cohorts, except for those from Bangladesh where the seroprevalence was significantly lower in younger migrant workers born after 1989. Conclusions The proportions having at least basic protection against diphtheria in migrant workers from five out of seven Asian countries (India, Indonesia, Malaysia, Myanmar and the Philippines) were higher than 85%, the threshold for diphtheria herd immunity. Seroprevalence surveys should be conducted periodically to assess the level of immunity against diphtheria and other vaccine preventable diseases in migrant worker population, so that appropriate interventions such as booster vaccination can be implemented proactively to prevent sporadic outbreaks.

Effectiveness of the CoronaVac® vaccine in a region of the Colombian Amazon, was herd immunity achieved?

Introduction Currently, more than 4.5 billion doses of SARS-CoV-2 vaccines have been applied worldwide. However, some developing countries are still a long way from achieving herd immunity through vaccination. In some territories, such as the Colombian Amazon, mass immunization strategies have been implemented with the CoronaVac® vaccine. Due to its proximity to Brazil, where one of the variants of interest of SARS-CoV-2 circulates. Objective To determine the effectiveness of the CoronaVac® vaccine in a population of the Colombian Amazon. Methods Between February 24, 2021, and August 10, 2021, a descriptive observational study was carried out in which a population of individuals over 18 years of age immunized with two doses of the CoronaVac® vaccine was evaluated. The study site was in the municipality of Mitú, Vaupés, in southeastern Colombia, a region located in the Amazon bordering Brazil. Results. 99% of the urban population of the Mitú municipality were vaccinated with CoronaVac®. To date, 5.7% of vaccinated individuals have become ill, and only 0.1% of these require hospitalization. One death was attributable to COVID-19 has been reported among vaccinated individuals, and the vaccine has shown 94.3% effectiveness against mild disease and 99.9% against severe infection. Conclusions The herd immunity achieved through mass vaccination in this population has made it possible to reduce the rate of complicated cases and mortality from COVID-19 in this region of the Colombian Amazon. Highlights CoronaVac® has shown 94.3% effectiveness against mild disease and 99.9% against severe infection in this indigenous population. CoronaVac® reduces the mortality rate from 2.2% in 2020 to 0.22% in 2021. The herd immunity was achieved through mass vaccination in this region of the Colombian Amazon.

Bayesian Inference of State-Level COVID-19 Basic Reproduction Numbers across the United States

Although many persons in the United States have acquired immunity to COVID-19, either through vaccination or infection with SARS-CoV-2, COVID-19 will pose an ongoing threat to non-immune persons so long as disease transmission continues. We can estimate when sustained disease transmission will end in a population by calculating the population-specific basic reproduction number , the expected number of secondary cases generated by an infected person in the absence of any interventions. The value of relates to a herd immunity threshold (HIT), which is given by . When the immune fraction of a population exceeds this threshold, sustained disease transmission becomes exponentially unlikely (barring mutations allowing SARS-CoV-2 to escape immunity). Here, we report state-level estimates obtained using Bayesian inference. Maximum a posteriori estimates range from 7.1 for New Jersey to 2.3 for Wyoming, indicating that disease transmission varies considerably across states and that reaching herd immunity will be more difficult in some states than others. estimates were obtained from compartmental models via the next-generation matrix approach after each model was parameterized using regional daily confirmed case reports of COVID-19 from 21 January 2020 to 21 June 2020. Our estimates characterize the infectiousness of ancestral strains, but they can be used to determine HITs for a distinct, currently dominant circulating strain, such as SARS-CoV-2 variant Delta (lineage B.1.617.2), if the relative infectiousness of the strain can be ascertained. On the basis of Delta-adjusted HITs, vaccination data, and seroprevalence survey data, we found that no state had achieved herd immunity as of 20 September 2021.

COVID-19 vaccine prioritization based on district classification in Yogyakarta Province, Indonesia

Due to limited availability, Indonesia’s coronavirus disease 2019 (COVID-19) vaccination will be done in 4 stages until herd immunity has been reached. Yogyakarta, an education and tourist destination, needs to get a specific, spatial estimation of the exact need for COVID-19 vaccination without delay. This study sheds light on identifying which districts should be prioritized at each vaccination phase. Secondary data collected from provincial, and county-level statistical agencies were quantitatively calculated by the Z-Score method. The results indicate that the first phase of vaccination should prioritize Pengasih and Sentolo districts in Kulon Progo Regency, which have a large number of health workers; the districts of Depok, Banguntapan, Piyungan, Sewon, Wonosari, Gamping, Mlati and Ngaglik should be done in the second phase based on the fact that these districts have many public service officials as well as elderly people; Umbulharjo and Depok districts will be approached in the third phase since they have more vulnerable groups and facilities that may promote COVID- 19 transmission during their daily activities; while the fourth phase should focus on the districts of Banguntapan, Sewon, Kasihan, Gamping, Mlati, Depok, and Ngaglik due to the intensity of COVID-19 clusters discovered there. Overall, vaccination would be given the priority in the districts with the largest number of people in need, i.e., public service officers, elderly people and those likely to be exposed to the coronavirus causing COVID-19.

Large-scale cross-sectional seroepidemiologic study of COVID-19 in Japan: Acquisition of herd immunity and the vaccines' efficacy

Background: The COVID-19 pandemic situation has been changing drastically worldwide due to the continuous appearance of SARS-CoV-2 variants and the roll-out of mass vaccination. Periodic cross-sectional studies during the surge of COVID-19 cases is essential to elucidate the pandemic situation. Methods: Sera of 1,000 individuals who underwent a health check-up in Hyogo Prefecture Health Promotion Association clinics in Japan were collected in August and December 2021. Antibodies against SARS-CoV-2 N and S antigens were detected in the sera by an electrochemiluminescence immunoassay (ECLIA) and an enzyme-linked immunosorbent assay (ELISA), respectively. The sera's neutralization activities for the conventional SARS-CoV-2 (D614G), Delta, and Omicron variants were measured. Results: The seropositive rates for the antibody against N antigen were 2.1% and 3.9% in August and December 2021 respectively, demonstrating a Delta variant endemic during that time; the actual infection rate was approximately twofold higher than the rate estimated based on the polymerase chain reaction (PCR)-based diagnosis. The anti-S seropositive rate was 38.7% in August and it reached 90.8% in December, in concordance with the vaccination rate in Japan. In the December cohort, 78.7% of the sera showed neutralizing activity against the Delta variant, whereas that against the Omicron was much lower at 36.6%. Conclusions: These analyses revealed that herd immunity against SARS-CoV-2 including the Delta variant was established in December 2021, leading to convergence of the variants. The low neutralizing activity against the Omicron variant suggests the need for the further promotion of the prompt three-dose vaccination to overcome this variant's imminent 6th wave in Japan.

Vaccination Schedule under Conditions of Limited Vaccine Production Rate

The paper is devoted to optimal vaccination scheduling during a pandemic to minimize the probability of infection. The recent COVID-19 pandemic showed that the international community is not properly prepared to manage a crisis of this scale. Just after the vaccines had been approved by medical agencies, the policymakers needed to decide on the distribution strategy. To successfully fight the pandemic, the key is to find the equilibrium between the vaccine distribution schedule and the available supplies caused by limited production capacity. This is why society needs to be divided into stratified groups whose access to vaccines is prioritized. Herein, we present the problem of distributing protective actions (i.e., vaccines) and formulate two mixed-integer programs to solve it. The problem of distributing protective actions (PDPA) aims at finding an optimal schedule for a given set of social groups with a constant probability of infection. The problem of distributing protective actions with a herd immunity threshold (PDPAHIT) also includes a variable probability of infection, i.e., the situation when herd immunity is obtained. The results of computational experiments are reported and the potential of the models is illustrated with examples.

Caveats on COVID-19 herd immunity threshold: the Spain case

After a year of living with the COVID-19 pandemic and its associated consequences, hope looms on the horizon thanks to vaccines. The question is what percentage of the population needs to be immune to reach herd immunity, that is to avoid future outbreaks. The answer depends on the basic reproductive number, R0, a key epidemiological parameter measuring the transmission capacity of a disease. In addition to the virus itself, R0 also depends on the characteristics of the population and their environment. Additionally, the estimate of R0 depends on the methodology used, the accuracy of data and the generation time distribution. This study aims to reflect on the difficulties surrounding R0 estimation, and provides Spain with a threshold for herd immunity, for which we considered the different combinations of all the factors that affect the R0 of the Spanish population. Estimates of R0 range from 1.39 to 3.10 for the ancestral SARS-CoV-2 variant, with the largest differences produced by the method chosen to estimate R0. With these values, the herd immunity threshold (HIT) ranges from 28.1 to 67.7%, which would have made 70% a realistic upper bound for Spain. However, the imposition of the delta variant (B.1.617.2 lineage) in late summer 2021 may have expanded the range of R0 to 4.02–8.96 and pushed the upper bound of the HIT to 90%.

Spatial clustering in vaccination hesitancy: the role of social influence and social selection

The phenomenon of vaccine hesitancy behavior has gained ground over the last three decades, jeopardizing the maintenance of herd immunity. This behavior tends to cluster spatially, creating pockets of unprotected sub-populations that can be hotspots for outbreak emergence. What remains less understood are the social mechanisms that can give rise to spatial clustering in vaccination behavior, particularly at the landscape scale. We focus on the presence of spatial clustering, and aim to mechanistically understand how different social processes can give rise to this phenomenon. In particular, we propose two hypotheses to explain the presence of spatial clustering: (i) social selection, in which vaccine-hesitant individuals share socio-demographic traits, and clustering of these traits generates spatial clustering in vaccine hesitancy; and (ii) social influence, in which hesitant behavior is contagious and spreads through neighboring societies, leading to hesitant clusters. Adopting a theoretical spatial network approach, we explore the role of these two processes in generating patterns of spatial clustering in vaccination behaviors under a range of spatial structures. We find that both processes are independently capable of generating spatial clustering, and the more spatially structured the social dynamics in a society are, the higher spatial clustering in vaccine-hesitant behavior it realizes. Together, we demonstrate that these processes result in unique spatial configurations of hesitant clusters, and we validate our models on both processes with fine-grain empirical data on vaccine hesitancy, social determinants, and social connectivity in the US. Finally, we propose, and evaluate the effectiveness of, two novel intervention strategies to diminish hesitant behavior. Our generative modeling approach informed by unique empirical data provides insights on the role of complex social processes in driving spatial heterogeneity in vaccine hesitancy.

Analyzing natural herd immunity media discourse in the United Kingdom and the United States

Natural herd immunity, where community-acquired infections in low-risk populations are used to protect high risk populations from infection–has seen high profile support in some quarters, including through the Great Barrington Declaration. However, this approach has been widely criticized as ineffective and misinformed. In this study, we examine media discourse around natural herd immunity in the United States (US) and United Kingdom (UK) to better understand how this approach was promoted. Country-specific news media publications between March 11, 2020 and January 31, 2021 were searched for references to herd immunity. News articles focused on herd immunity and including a stakeholder quote about herd immunity were collected, resulting in 400 UK and 144 US articles. Stakeholder comments were then coded by name, organization, organization type, and concept agreement or disagreement. Government figures and a small but vocal coalition of academics played a central role in promoting natural herd immunity in the news media whereas critics were largely drawn from academia and public health. These groups clashed on whether: natural herd immunity is an appropriate and effective pandemic response; the consequences of a lockdown are worse than those of promoting herd immunity; high-risk populations could be adequately protected; and if healthcare resources would be adequate under a herd immunity strategy. False balance in news media coverage of natural herd immunity as a pandemic response legitimized this approach and potentially undermined more widely accepted mitigation approaches. The ability to protect high risk populations while building herd immunity was a central but poorly supported pillar of this approach. The presentation of herd immunity in news media underscores the need for greater appreciation of potential harm of media representations that contain false balance.