Abstract
Objective To evaluate the effectiveness of heterologous and homologous covid-19 vaccine regimens with and without boosting in preventing covid-19 related infection, hospital admission, and death.
Design Living systematic review and network meta-analysis.
Data sources World Health Organization covid-19 databases, including 38 sources of published studies and preprints.
Study selection Randomised controlled trials, cohort studies, and case-control studies.
Methods 38 WHO covid-19 databases were searched on a weekly basis from 8 March 2022. Studies that assessed the effectiveness of heterologous and homologous covid-19 vaccine regimens with or without a booster were identified. Studies were eligible when they reported the number of documented, symptomatic, severe covid-19 infections, covid-19 related hospital admissions, or covid-19 related deaths among populations that were vaccinated and unvaccinated. The primary measure was vaccine effectiveness calculated as 1odds ratio. Secondary measures were surface under the cumulative ranking curve (SUCRA) scores and the relative effects for pairwise comparisons. The risk of bias was evaluated by using the risk of bias in non-randomised studies of interventions (ROBINS-I) tool for all cohort and case-control studies. The Cochrane risk of bias tool (version 2; ROB-2) was used to assess randomised controlled trials.
Results The first round of the analysis comprised 53 studies. 24 combinations of covid-19 vaccine regimens were identified, of which a three dose mRNA regimen was found to be the most effective against asymptomatic and symptomatic covid-19 infections (vaccine effectiveness 96%, 95% credible interval 72% to 99%). Heterologous boosting using two dose adenovirus vector vaccines with one mRNA vaccine has a satisfactory vaccine effectiveness of 88% (59% to 97%). A homologous two dose mRNA regimen has a vaccine effectiveness of 99% (79% to 100%) in the prevention of severe covid-19 infections. Three dose mRNA is the most effective in reducing covid-19 related hospital admission (95%, 90% to 97%). The vaccine effectiveness against death in people who received three doses of mRNA vaccine remains uncertain owing to confounders. In the subgroup analyses, a three dose regimen is similarly effective in all age groups, even in the older population (65 years). A three dose mRNA regimen works comparably well in patients who are immunocompromised and those who are non-immunocompromised. Homologous and heterologous three dose regimens are effective in preventing infection by covid-19 variants (alpha, delta, and omicron).
Conclusion An mRNA booster is recommended to supplement any primary vaccine course. Heterologous and homologous three dose regimens work comparably well in preventing covid-19 infections, even against different variants. The effectiveness of three dose vaccine regimens against covid-19 related death remains uncertain.
Systematic review registration This review was not registered. The protocol is included in the supplementary document.
Readers note This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication.
The covid-19 pandemic caused by SARS-CoV-2 has led to more than 489 million confirmed cases and six million deaths worldwide according to the World Health Organization covid-19 weekly epidemiological update on 5 April 2022.1 Vaccination remains an important preventive measure against covid-19. Since the rollout of covid-19 vaccines in late 2020, global vaccine administration has accumulated up to 11 billion doses, with 13.08 million being administered daily.2 WHO has authorised the emergency use of 10 vaccines developed by Janssen, Bharat Biotech, Pfizer-BioNTech, Oxford-AstraZeneca, Moderna, Sinopharm, Sinovac, Novavax, and Serum Institute of India.3 Despite a rapid decline in the number of covid-19 symptomatic infections and deaths, several studies have raised concerns about waning vaccine induced immunity in vaccinated populations due to time and the emergence of covid-19 variants, which prompts the urgent need for a booster dose.45678 Furthermore, heterologous vaccine regimens could be an alternative strategy to homologous regimens when supplies are limited. Inconsistent covid-19 vaccine procurement and limited vaccine supply have resulted in certain vaccine types being unavailable in clinical settings.910 Research that evaluates different vaccine regimens will aid decision making in public health policy and reduce vaccination hesitancy.
On 16 December 2021, WHO released interim guidance summarising the existing evidence on heterologous covid-19 vaccine schedules and gave recommendations for these schedules.11 Although recent observational studies and systematic reviews have respectively assessed the clinical efficacy of covid-19 vaccines and provided a descriptive qualitative overview of various heterologous regimens, a quantitative comparison of different vaccine regimens against the original and new circulating variants of concern (such as omicron BA.1 and BA.2) is urgently needed.1213 Such a comparison is particularly important because randomised controlled trials that involve several vaccine types need to be multinational in scale and data are not readily available. Additionally, the effectiveness of a mixed combination of covid-19 vaccines remains uncertain. Quantitative systematic analyses of different vaccine regimens and a dynamic platform to monitor the effectiveness of various vaccine regimens in protecting against future variants of concern are urgently needed.
We compared the vaccine effectiveness of heterologous and homologous regimens with and without boosting in our living systematic review and network meta-analysis. Our study supplemented WHOs summary report by quantitatively evaluating different covid-19 vaccine regimens: heterologous prime boost, single dose, homologous two dose, heterologous and homologous third dose boosting, with the no-vaccine group as a reference. The advantage of a network meta-analysis compared with a conventional meta-analysis is the high comparability of direct and indirect evidence, which enables vaccine effectiveness to be compared across pairs of studies, resulting in a more comprehensive interpretation of the available evidence. With network meta-analysis, we were able to summarise the effectiveness of all available covid-19 vaccine regimens and determine the relative effects of various primary and boosting regimens as assessed in current clinical trials.
Overall, our study will serve as a monitoring platform for informing the public and health officials about the vaccine effectiveness of all WHO recommended vaccines and their homologous and heterologous regimen combinations against circulating SAR-CoV-2 (current and future variants of concern). This study is ongoing and will be updated through this living systematic review.
This living systematic review and network meta-analysis followed the preferred reporting items for a systematic review and meta-analysis of network meta-analysis (PRISMA-NMA). Supplementary table 9 presents the PRISMA-NMA checklist.
We searched 38 WHO covid-19 databases for published studies and preprint databases on a weekly basis from 8 March 2022. No language restrictions were applied to the search. Supplementary table 1 gives the full search strategy. We followed prespecified inclusion criteria during study screening (supplementary protocol 2.1): studies that assessed the efficacy or effectiveness of covid-19 vaccines in humans; studies that investigated documented, symptomatic, severe covid-19 infections, covid-19 related hospital admissions, or covid-19 related deaths; commentaries, editorials, and correspondence were included if sufficient data were provided in a supplementary file. Populations of all ages and both sexes were included in this analysis. Age was stratified into three groups: young (<18 years), adult (18-64 years), and older (65 years). Exclusion criteria were applied in the network meta-analysis: one arm studies were excluded; studies that did not report vaccine efficacy or effectiveness were excluded.
WYA and PPHC independently performed a study search and screened titles and abstracts of all retrieved studies in EndNote 20. Retrieved studies were further assessed for eligibility using full text screening by the same reviewers. All disagreements were resolved by consensus between WYA and PPHC. Duplicated results were removed upon reference importation in EndNote 20 by WYA. Any remaining duplicates were eliminated manually.
For every eligible study identified from full text screening, WYA and PPHC independently extracted information on the study characteristics: author and year, participant eligibility, age of participants, the proportion of male participants, distribution of baseline characteristics, vaccine priority groups, ethnicity, country of study, SARS-CoV-2 variants of concern investigated, an overall sample size of the study, trial registry for randomised controlled trials, study design, research aim, intervention group (treatment 1), comparator group (treatment 2), dose interval, follow-up period, clinical outcome assessed, and outcome measures (supplementary table 2). WYA and PPHC also extracted the respective number of events in the intervention and comparator groups and reported vaccine efficacy or effectiveness. When the number of events was not provided, the figure was derived using the reported odds ratio, risk ratio, incidence rate ratio, or hazard ratio, given that the total number of participants in each intervention and comparator group was known. For studies that recorded the number of events at two or more time points, data were extracted for the period when the vaccine was the most effective.
We estimated the overall effectiveness of each vaccine regimen (1odds ratio). We created league tables that present relative effects in pairwise comparisons with 95% credible intervals. To rank the vaccination regimens with different combinations of vaccines, we determined the surface under the cumulative ranking curve (SUCRA) scores. To combine randomised and non-randomised evidence in the network meta-analysis, we estimated treatment effects using a three level bayesian hierarchical modelling approach with random effects (supplementary protocol 2.4.2).1415 We assumed that all studies shared a common heterogeneity variance. Vague priors were used for heterogeneity variance and treatment effect estimates. The number of iterations, burn-in, and adaptation used in the Markov chain Monte Carlo method is described in the protocol. JAGS was used to implement the bayesian hierarchical model.16 BUGS codes were provided on GitHub (https://github.com/wyauac/NMA-of-heterologous-and-homologous-vaccine-effectiveness).
Network meta-analysis was performed twice, each with nodes defined in two different waysvaccine product based and platform basedproviding two perspectives on vaccine effectiveness. For the vaccine product based network, a node was made of vaccines of the same brand with the same number of doses. For the platform based network, vaccines of the same platform but different brands were grouped into the same nodes, given the number of doses was the same. Inconsistency in the networks was evaluated using the guideline developed by Daly and colleagues.17 Finally, we performed subgroup analyses by reanalysing studies that investigated the variable of interest (age, ethnicity, immunocompromised or not, or covid-19 variant) with all other factors controlled. Sensitivity analysis was done by restricting the analysis to low risk of bias studies.
For quality assessment of non-randomised trials, the risk of bias within individual studies was evaluated using the ROBINS-I tool (risk of bias in non-randomised studies of interventions), which was recommended by Cochrane reviews.18 The ROB-2 tool (Cochrane risk of bias version 2) was used to assess randomised controlled trials.19 We assessed the quality of the evidence by applying the GRADE method (grading of recommendations assessment, development, and evaluation) and gave a rating to each estimate obtained in our network meta-analysis.20 Publication bias in our analysis was assessed through a comparison adjusted funnel plot. Each data point in the funnel represented a pair of comparisons of treatments instead of a single study.21 The plot was drawn with the function netmeta::funnel.
Many discussions with the public, such as the media, doctors, and patients, on their queries on the need for a booster vaccine dose have inspired this review. However, there is no direct patient and public involvement because our analysis does not require their involvement. We spoke to patients with covid-19 about the study, and we asked several public members to read our article after submission.
Study selection followed PRISMA-NMA guidelines (fig 1). We identified 12962 studies from 38 databases and removed 5559 duplicates, retaining 7403 studies for full text screening. We excluded 6923 studies by title, abstract, and subheading screening, of which 3007 (43.4%) were non-vaccine studies, and 1398 (20.2%) were studies of viruses other than SARS-CoV-2, 800 (11.6%) were reviews, and 502 (7.3%) investigated non-human subjects. The remaining 1216 studies (17.6%) were descriptive literature with no supplementary data. During the full text screening and data extraction, we excluded 404 studies. Twenty seven (6.7%) were protocols, seven (1.7%) were vaccine safety studies, and 370 (91.6%) only examined immunogenicity and reactogenicity in people who were vaccinated. Of the remaining 76 studies, we were able to extract data from 53,2223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374 which gave us a sample size of 100190476 participants from 15 countries. Supplementary table 2 presents a summary of the study characteristics. Eight studies included participants older than 652731434748556869 and seven studies enrolled participants younger than 18.45535760616873 Seven studies included high risk populations (defined as having more than one chronic condition),27404143474869 of which two studies included patients who were immunocompromised in a subset of the high risk populations.4869 Of the 53 included studies, 19 investigated the protectiveness of vaccines against covid-19 variants of concern or variants of interest, including alpha (B.1.1.7), beta (B.1.351), gamma (P.1), delta (B.1.617.2), and omicron (B.1.1.529).22263032343738394142444748495761636870
Flowchart of study selection
We evaluated the risk of bias by following instructions in ROB-2 for randomised controlled trials and ROBINS-I for non-randomised studies.1819 Of the 37 non-randomised studies, 16 were rated to have a moderate risk of bias, mainly because they did not control for confounders such as comorbidities and other baseline characteristics.22323334353738444650566061656874 Nine studies from the same pool were also prone to high selection bias for having an imbalanced proportion of participants of different ages and sexes.223233343537505661 Three non-randomised studies relied on surveillance data, which were subject to incomplete information, and so received a moderate risk of bias score in the domain of bias due to missing data.384668 Finally, one study was rated as having a severe bias in selecting the reported result because the authors reported the overall vaccine effectiveness for mRNA vaccines instead of the specific vaccine products investigated in the study.44 All randomised controlled trials were considered low risk of bias except for three studies in which participants were unblinded after the second dose.404347 Supplementary figure 2 and supplementary table 4 show the results of ROB-2 and ROBINS-I.
There were two network analyses in this study: vaccine product based and platform based. In the vaccine product based network, we identified 24 covid-19 vaccine combinations from the 53 included studies and coded them by the number of doses used and the acronym of the vaccines (supplementary table 3). For example, 1AZ1BNT represented a heterologous prime boost regimen using ChAdOx1 (Oxford-AstraZeneca) as the first dose and BNT162b2 (Pfizer-BioNTech) as the second dose. In the platform based network, we identified 13 vaccine regimens where vaccine products of the same platform were grouped into the same node in the second network. Network diagrams for all five outcomes were drawn to depict the relation between all regimens. Most studies compared mRNA vaccines in the vaccine based and platform based networks, as indicated by the thickest lines (supplementary fig 1A-J). There was no disconnection between nodes.
Thirty five studies contributed to the investigation of vaccine effectiveness against documented covid-19 infections, of which 11 were randomised controlled trials. Supplementary tables 5 and 6 present the results of relative treatment effects for all pairwise comparisons of vaccine regimens. The odds ratios of all regimens analysed are smaller than 1 compared with the no-vaccine group, indicating that any vaccine regimen can confer protection against covid-19 infections, either asymptomatic or symptomatic. For three dose regimens in the vaccine product based network, two dose BNT162b2 with one mRNA-1273 (Moderna) booster is the most effective regimen (odds ratio 0.022, 95% credible interval 0 to 2.914), followed by three dose BNT162b2 (0.036, 0 to 3.033). However, the actual estimate for three dose homologous BNT162b2 is uncertain due to selection bias in one study that assessed BNT162b2 regimens.32 A two dose CoronaVac (Sinovac) with one dose BNT162b2 regimen is also highly effective (0.046, 0.004 to 0.567). Among the two dose regimens, heterologous primary vaccination with ChAdOx1 and BNT162b2 is more effective than two dose BNT162b2 or two dose mRNA-1273, with an average odds ratio difference of 0.04 (supplementary table 5A).
In the platform based network, three dose mRNA and two dose inactivated vaccine with one dose mRNA regimens are comparably effective (0.046, 0.009 to 0.275 for homologous mRNA; 0.047, 0.003 to 0.675 for heterologous inactivated). Two dose adenovirus with one dose mRNA is slightly less effective but prevents covid-19 better than any homologous two dose regimens (0.066, 0.007 to 0.541 for heterologous adenovirus; supplementary table 6A). One dose regimens (mRNA or adenovirus vector or protein based) are less protective than two dose regimens (mRNA or adenovirus vector or inactivated or protein based). Table 1 shows the SUCRA scores.
Ranking of vaccine regimens
We were able to pool results from 23 studies that evaluated the vaccine effectiveness against symptomatic covid-19 infections, of which three studies assessed the effect of homologous boosters with BNT162b2, mRNA-1273, or ChAdOx1.252632 The odds ratios between a homologous booster dose and the no-vaccine group are 0.175 (95% credible interval 0.021 to 1.388), 0.104 (0.016 to 0.733), and 0.147 (0.017 to 1.240) for three dose mRNA-1273, three dose BNT162b2, and three dose ChAdOx1, respectively (supplementary table 5B). Three dose mRNA-1273 and three dose ChAdOx1 are more effective than the two dose homologous regimen of mRNA-1273 and ChAdOx1 with reference to the no-vaccine group. In the platform based network, three dose mRNA is shown to be the most effective among all regimens (0.019, 0.002 to 0.136; supplementary table 6B). The one dose protein based regimen appeared to be highly effective (0.094, 0.001 to 10.134). Still, the studies that investigated this regimen were found to be confounded by unblinding and unexplained censoring of data.4047 Therefore, certainty in the estimate for a one dose protein based vaccine regimen is low.
We analysed 12 studies for vaccine effectiveness against severe covid-19 infections. With reference to the no-vaccine group, all one dose regimens are less effective than two dose and three dose regimens, of which one dose Ad26.cov2.S (Janssen) and one dose CoronaVac had no association with a reduction of severe covid-19 infections (odds ratio>1; supplementary table 5C). Three dose BNT162b2 was more effective compared with any vaccine regimens (odds ratio<1 in all comparisons; supplementary table 5C).
Seventeen studies were evaluated for vaccine effectiveness against covid-19 related hospital admissions. Individuals receiving three dose BNT162b2 or three dose mRNA-1273 are the least likely to be admitted to hospital because of covid-19 (odds ratio 0.054, 95% credible interval 0.010 to 0.294 for three dose BNT162b2; and 0.018, 0.001 to 0.291 for three dose mRNA-1273; supplementary table 5D). Results showed that heterologous primary vaccination of ChAdOx1 with BNT162b2 is not as effective as two dose homologous BNT162b2, mRNA-1273, or ChAdOx1 regimens (0.515, 0.091 to 3.291 for heterologous primary ChAdOx1 with BNT162b2; supplementary table 5D). However, the estimates for two dose BNT162b2 and mRNA-1273 could be biased by confounders in the studies that assessed them; therefore, the true estimates of odds ratios for the two dose homologous mRNA vaccine regimens might be higher. Studies that reported covid-19 hospital admissions are mainly observational, which also adds uncertainty to the estimates.
Eight studies were evaluated for vaccine effectiveness against covid-19 related deaths. Estimates for the prevention of deaths are highly uncertain because observational studies were the only evidence available in this analysis. None of the randomised controlled trials reported deaths. Results could be confounded by age and disease conditions, leading to highly uncertain estimates.
Owing to high uncertainty in the estimates of vaccine effectiveness and limited data availability for severe covid-19, hospital admissions, and deaths, we only performed subgroup analyses on studies that investigated non-severe SARS-CoV-2 infections, asymptomatic and symptomatic. We were able to stratify studies by age, being immunocompromised or not, and covid-19 variants. Sex and ethnicity were not investigated because of limited data.
We found that three dose regimens conferred protection to all age groups (young, adult, and older). However, the young group appeared to have slightly better immunity than the adult group (odds ratio difference 0.02) and the older group (odds ratio difference 0.07) after receiving a three dose regimen (supplementary table 8A). On average, the vaccine effectiveness of any regimen was lowest in the older group. A two dose CoronaVac regimen was found to have no association with covid-19 infections in the older group (odds ratio 1.13, 95% credible interval 0.22 to 16.92; supplementary table 8A). Supplementary table 8B shows comparisons of vaccine effectiveness in patients who are immunocompromised. A three dose mRNA regimen worked comparably well in the non-immunocompromised and immunocompromised groups. However, the effect of two dose mRNA vaccines is weaker in those who are immunocompromised than in those who are non-immunocompromised (supplementary table 8B).
For the covid-19 variant subgroups, sufficient data were only available to analyse alpha, delta, and omicron variants. Vaccine regimens with two or more doses were found to be effective against the alpha variant. The effectiveness of three dose vaccine regimens within variants is comparable; however, effectiveness between variants differs considerably. The three dose regimens are less effective in preventing delta and omicron infections (supplementary table 8C). All one dose and two dose regimens appear to be ineffective against omicron. The estimates in the variant subgroups could be underestimated owing to a surge in confirmed infections during the outbreak of omicron; therefore, we have low certainty on the true vaccine effectiveness against this variant. We reanalysed the vaccine effectiveness in a sensitivity analysis without all high risk of bias studies. Table 2 shows the results.
Odds ratios (95% credible intervals) and vaccine effectiveness of vaccine regimens by platform with only low risk of bias studies
We assessed inconsistency in the vaccine product based and platform based networks by comparing residual deviance between the inconsistency and consistency model. The deviance contribution plot shows some points below the line of equality (supplementary fig 3A, B). Further assessment of inconsistency was done using the node splitting model (supplementary table 7).
Publication bias was examined by using the comparison adjusted funnel plot. We hypothesised that published studies tend to report better results than unpublished studies. A comparison adjusted funnel plot coupled with Eggers test was used to detect a small study effect (supplementary fig 4). Although a few estimates were lying away from the centre, Eggers test P value indicated that statistical significance was not reached (P=0.08).
Since the launch of covid-19 vaccines in 2020, research efforts have been made to investigate different combinations of covid-19 vaccines as alternatives to homologous regimens. This review has provided a comprehensive analysis of the effectiveness of WHO approved vaccines and compared all available vaccine regimens. We assessed vaccines of different brands and platforms. Comparisons by platforms are more informative and translatable into practice because vaccines from different manufacturers have been shown to have similar efficacy in phase trials.274041454755637173 Our findings will serve as a reference for clinicians, public health policy makers, and researchers for vaccine related purposes, such as making recommendations to patients and public health decision making.
We compared the vaccine effectiveness in preventing five outcomes: covid-19 related documented infections, symptomatic infections, severe infections, and covid-19 related hospital admissions and deaths. We have higher certainty in the evidence relating to covid-19 infections than for covid-19 related hospital admissions and deaths owing to a high risk of bias and imprecision. We have low certainty in the true estimates for vaccine effectiveness against the omicron variant because the relevant studies were conducted during the omicron outbreak. However, we are confident that a three dose regimen will effectively prevent covid-19 variants. The results have consistently shown a considerable reduction in covid-19 infections across different variants, despite the studies conducted during the peak of infections.
Three dose mRNA vaccines (three dose BNT162b2 or mRNA-1273) appear to be the most effective in preventing non-severe covid-19 infections. A heterologous regimen with an mRNA booster in recipients of two dose adenovirus vector vaccines also has 80% protection against covid-19. Among all two dose regimens, mRNA vaccines remain the gold standard for prevention against all covid-19 related outcomes, although we have moderate certainty in the actual effectiveness against hospital admission caused by covid-19. Our results imply that mRNA vaccines will continue to be the preferred vaccine type, either as primary vaccines or booster doses. When comparing vaccine effectiveness between age groups, we found people younger than 18 have a lower chance of covid-19 infection after receiving vaccines of any platform. This finding agrees with a recent immunogenicity study in children and adolescents.75 We also found that a heterologous or a homologous third dose booster can confer an equal level of protection in all age groups, even in the older group (65). If several boosters are administered to any age group, a heterologous or homologous regimen will not make much difference in immunity improvement. Importantly, we discovered that any homologous or heterologous three dose regimen induces a considerably higher level of immunity in older people than a two dose homologous regimen, which is comparable to that seen in all other age groups.
In the vaccine effectiveness comparison between immunocompromised and non-immunocompromised groups, we found that all vaccine regimens have lower effectiveness in people who are immunosuppressed or immunodeficient, with a decrease of 2% vaccine effectiveness. Similarly, a review paper has shown weaker vaccine induced immunity among people who are immunocompromised, such as lower seroconversion rates.76 Our review suggests that a third booster dose, as part of a heterologous or homologous regimen, will greatly improve protection in these patients compared with a two dose primary vaccination. This finding orthogonally agrees with a randomised trial that studied SARS-CoV-2 antibody seroconversion in people who were immunocompromised and received a heterologous or homologous booster after primary mRNA vaccination. Therefore, the number of doses of vaccines seems to be the key to improving immunity rather than the combinations of vaccine types.77
Rapidly evolving viral strains continually pose challenges to the elimination of covid-19. Recent immunogenicity research has reported waning vaccine effectiveness against delta and omicron variants.78 Our estimates showed that the two dose and one dose regimens were ineffective against the omicron variant. These estimates are in line with the findings on omicron variant neutralisation after a homologous two dose mRNA regimen.79 However, our study shows that homologous and heterologous three dose regimens successfully reduce covid-19 infections caused by the omicron variant. One study has shown that people receiving an mRNA booster after two doses of CoronaVac have a 1.4-fold increase in neutralisation activity against omicron.80 Therefore, boosting vaccination will effectively control the spread of covid-19 variants. The latest study of the fourth dose of BNT162b2 reported that effectiveness against confirmed infection and severe covid-19 improves from receiving a third dose to a fourth dose in people aged 60 or older.81 This finding implies that ongoing vaccine campaigns will be needed to prevent covid-19 infections in the long term. According to our results, mRNA vaccines appear to be the preferred choice for any additional dose.
Although we could not pool the results from 23 studies, all studies suggested that people who received a third dose mRNA or heterologous boosting regimen are less likely to get infected by SARS-CoV-2 than those receiving only a primary homologous regimen. When considering the safety of heterologous and booster vaccines, one study that assessed the safety and reactogenicity of heterologous primary vaccination with mRNA, adenovirus vector, and protein based vaccines showed no safety concerns.82 Another study that examined the safety of booster doses in adults also showed fewer local and systemic reactions after a homologous mRNA booster than after a two dose homologous regimen.83
Our study did not evaluate the optimum time interval for prime boost or boosting regimens owing to limited information about the dynamics of vaccine effectiveness across a period in a few studies. However, we anticipate more longitudinal research on the varying infection rates among people who are vaccinated and those who are not vaccinated. This type of study that combines timely measurement of antibody titres will provide more evidence on how the impact of vaccination changes over time and the protection period of a series of vaccinations.
A three dose mRNA regimen seems to be the most effective in preventing covid-19 infections. An mRNA booster can induce a similar level of protection against covid-19 infections to homologous primary vaccination. A third dose vaccine is needed to prevent covid-19 variant infections. Heterologous and homologous three dose regimens work equally well in preventing any covid-19 infections, even variants. We will update the results when newly published studies or preprints become available. For example, we will add other vaccine types and multiple dose regimens to the analysis as more vaccines are approved by the WHO emergency use listing. More research on multiple doses of the primary vaccination is expected. We will also examine the efficacies of vaccine regimens against new variants for the general population and other subgroups, such as sex, ethnicity, and other high risk populations.
The efficacy and effectiveness of individual vaccine products for covid-19 and its variants of concern are well known
Research on the effectiveness of vaccine combinations, especially for particular populations such as older people and those who are immunocompromised, is lacking
This living systematic review and network meta-analysis investigated the effectiveness of different homologous and heterologous vaccine regimens with and without boosting against covid-19 infections and covid-19 related hospital admissions and deaths
An mRNA booster to any primary vaccination included in our study confers a high level of protection similar to a homologous three dose mRNA regimen; a third dose is needed to prevent infection caused by the omicron variant
Any homologous or heterologous three dose regimen induces higher immunity in people 65 than a two dose homologous regimen; a three dose mRNA regimen reduces the risk of asymptomatic or symptomatic covid-19 infections in the immunocompromised population
COVID-19 Vaccines Most Effective in Patients With Myeloma and Gastrointestinal, Lung Cancers Cancer Therapy Advisor
If you recently contracted COVID, how long are you protected and are you at risk of getting the virus again?
The question has been asked since the start of the pandemic, but as the virus continues to mutate, the answers have changed.
Omicron, for example, led to a major shift in "natural immunity," with many who had previously been infected susceptible to reinfection with the new version of the virus.
Now, as omicron makes up nearly all U.S. COVID cases, it's a question of how protection from one version of omicron will work against newer subvariants.
"At the beginning, we could very confidently, you know, sort of back in February, we could really confidently say that 90% of the people were not getting reinfected if they had COVID already," Chicago Department of Public Health Commissioner Dr. Allison Arwady said last week. "That's been dropping a little bit though around the world."
According to the Centers for Disease Control and Prevention, "after recovering from COVID-19, most individuals will havesome protection from repeat infections."
"However, reinfections do occur after COVID-19," the CDC states, adding that changes and mutations "can lead to theemergence of variantsthat can increase the risk of reinfection."
Last month, Chicago's top doctor said experts were seeing changes in immunity from infection.
"We are seeing people get COVID still, more of these what we call breakthrough infections," Chicago Department of Public Health Commissioner Dr. Allison Arwady said. "But importantly, 'natural immunity' also is not lasting. And so we know that when somebody has had COVID, it's as much about how recently they've had it in some ways, because we are still seeing pretty good protection if somebody had one version of omicron. But we are starting to see, as omicron has continued to evolve, we're starting to see some more people who had original omicron even in December, even getting some of these these new subvariants of omicron."
While such cases aren't the norm, Arwady said, they are starting to rise.
"If you have had COVID in the last few months, your production is pretty good, but we're starting to see some more there," she said.
Currently, Chicago and several surrounding counties remain under a "high community level" for COVID, per guidelines set by the CDC.
But Arwady also warned last week that people should not "try to 'get COVID to get it over with,'" in part because it remains unclear if they could still contract the virus after infection.
"Don't think that getting COVID means you'll never get COVID again," she said. "We see plenty of people get re-infected with COVID. The vaccine is the most important thing for protection."
The uncertainty surrounding natural immunity can be particularly confusing for those experiencing long COVID symptoms.
The CDC says most people with COVID-19 "get better within a few days to a few weeks after infection." But for some, symptoms may last even longer and in other cases may even disappear and then return.
"Post-COVID conditions can include a wide range of ongoing health problems," the CDC states. "These conditions can last weeks, months, or years."
A recent study from Northwestern Medicine showed that many so-called COVID "long-haulers" continue to experience symptoms including brain fog, tingling, headaches, dizziness, blurred vision, tinnitus and fatigue an average of 15 months after the onset of the virus.
"Long-haulers, are defined as individuals who have had COVID symptoms for six or more weeks,the hospital system has said.
But, according to the CDC, four weeks after infection is when post-COVID conditions could first be identified.
"Most people with post-COVID conditions experienced symptoms days after their SARS CoV-2 infection when they knew they had COVID-19, but some people with post-COVID conditions did not notice when they first had an infection," the CDC states.
Long-COVID symptoms can range from a wide variety of ailments, some of which may even disappear and then return later.
"Post-COVID conditions may not affect everyone the same way. People with post-COVID conditions may experience health problems from different types and combinations of symptoms happening over different lengths of time," the CDC reports. "Most patients symptoms slowly improve with time. However, for some people, post-COVID conditions may last months, and potentially years, after COVID-19 illness and may sometimes result in disability."
Testing can also become challenging for such groups as PCR tests can "stay positive for some time," experts said.
"Those PCR tests are very sensitive," Arwady said. "They keep picking up dead virus in your nose for sometimes for weeks, but you can't grow that virus in the lab. You can't spread it but it can be positive."
According to theCDC, some people who contract COVID-19 can have detectable virus for up to three months, but that doesn't mean they are contagious.
Public health officials recommend that even those who contract COVID remain up-to-date with their vaccinations and booster shots.
"I think realistically, this is a guess, but my guess - where we're heading, given that there's no sign yet that COVID has stopped mutating...we've got to keep it from turning into hospitalizations and deaths, which are actually pretty good at already between vaccines and treatments," Arwady said. "But I do think it's likely that in the fall, we probably will see an updated version of a booster that actually has been changed to be more protective against the ways in which COVID has mutated since then."
THURSDAY 6/2/2022 2:01 p.m.
The Wisconsin Department of Health Services has reported 1,477,724 total positive coronavirus test results in the state and 13,026 total COVID-19 deaths.
The number of known cases per variant is no longer tracked as The Wisconsin Department of Health Services has updated its website, deleting that section.
Unable to view the tables below?Click here.
The DHS announced an attempt to verify and ensure statistics are accurate, some numbers may be subject to change. The DHS is combing through current and past data to ensure accuracy.
Wisconsins hospitals are reporting, that the 7-day moving average of COVID-19 patients hospitalized was 427 patients. Of those,45 are in an ICU. ICU patients made up 10.6%of hospitalized COVID-19 patients.
The Wisconsin Department of Health Services reports that 9,529,383 vaccine doses and 2,040,554 booster doses have been administered in Wisconsin as of June 2.
Unable to view the tables below?Click here.
The Wisconsin Department of Health Services is using a new module to measure COVID-19 activity levels. They are now using the Center for Disease Control and Preventions (CDC) COVID-19 Community Levels. The map is measured by the impact of COVID-19 illness on health and health care systems in the communities.
The Center for Disease Control and Prevention (CDC) reports that 10 counties in Wisconsin are experiencing high COVID-19 community levels. None of them are located in northeast Wisconsin.
24 counties in Wisconsin are experiencing medium COVID-19 community levels, including Brown, Door, Marinette, Menominee, and Winnebago County in northeast Wisconsin.
Every other county in Wisconsin is experiencing low COVID-19 community levels.
For more information on how the data is collected, visit the CDCs COVID-19 Community Levels data page.
A new virus outbreak is detected. It starts spreading around the globe, case by case, country by country. Health authorities launch into action, tracking infections and issuing guidance.
"This is not Covid," Dr. Jennifer McQuiston, a veterinarian and deputy director of the CDC's Division of High Consequence Pathogens and Pathology, said in a statement last week.
Of course, several leaders tried to calm citizens when Covid-19 was first emerging, only for that virus to spiral into a once-in-a-generation pandemic.
So how, exactly, is monkeypox different to Covid -- and why are experts so far more relaxed about this outbreak?
Most importantly, monkeypox is not spread as easily as Covid-19. "Respiratory spread is not the predominant worry" with monkeypox, McQuiston said. It's only passed between humans if there is very close contact with an infected person -- such as sharing clothing or bedding, or through saliva -- according to the World Health Organization (WHO).
However, in the developed world, "it would be very unusual to see anything more than a handful of cases in any outbreak, and we won't be seeing (Covid)-style levels of transmission," Head said.
But perhaps most importantly of all, monkeypox is not a new disease. Smallpox vaccines can be used to tackle the virus, there is a wealth of scientific research into how the illness acts, and it doesn't mutate as rapidly as Covid-19 has.
So if headlines about monkeypox transport your mind back to March 2020, it's worth taking a beat.
"This is a virus we understand: we have vaccines against it, we have treatments against it, and it's spread very differently than SARS-Cov-2 -- it's not as contagious as Covid -- so I am confident we're going to be able to keep our arms around it," White House Covid-19 Response Coordinator Dr. Ashish Jha told ABC's Martha Raddatz Sunday.
YOU ASKED. WE ANSWERED.
Q: Is Covid-19 contagious after treatment with Paxlovid?
A: People who have a Covid-19 relapse after being treated with antiviral drug Paxlovid can still be contagious, but they might not know it if they don't have any symptoms.
"People who experience rebound are at risk of transmitting to other people, even though they're outside what people accept as the usual window for being able to transmit," said Dr. Michael Charness of the Veterans Administration Medical Center in Boston.
Charness and his colleagues collaborated with a team of researchers at Columbia University to look into cases of Covid-19 that return after Paxlovid treatment. He said they've found at least two instances in which people have transmitted the virus to others when their infection recurs.
READS OF THE WEEK
Shanghai is finally 'reopening,' but the trauma of lockdown lives on
The skyscrapers lit up, roads filled with traffic, and young people drank and danced in the streets as fireworks boomed overhead.
As of Wednesday morning, most of Shanghai's 25 million residents are free to leave their communities, shops and office buildings can reopen, cars are back on the streets, and subway and buses are resuming services.
Did Covid curb your dating life? Date night will make its comeback a success
The pandemic may have seemed like the perfect opportunity to nurture a relationship with unlimited access to your partner, nonstop togetherness and plenty of time for intimacy.
But, as most of us are aware, lockdowns had the opposite effect on romance. Living on top of each other, not changing out of our pajamas and sometimes not showering was the epitome of not sexy.
Sex therapist Madelyn Esposito-Smith said that Covid-19 had "incinerated sexual desire" for couples living together, taking away all "intrigue and mystery" and making alone time a "precious commodity."
North Korea may rethink restrictions after claiming its Covid outbreak is improving
KCNA reported on Sunday that leader Kim Jong Un and other top officials had assessed the pandemic situation as "improved" and discussed adjusting containment measures.
Pyongyang reported more than 89,500 new "fever cases" and 106,390 recoveries between Friday and Saturday evening nationwide, but did not mention if there had been any additional deaths.
According to KCNA, the country's latest death toll stood at 69 at the end of last week. However, given the lack of independent reporting inside North Korea, it is difficult to verify the figures and there has long been widespread skepticism over the country's Covid reporting.
TOP TIP
If you suffer from long Covid, take it easy
If you don't feel well in the weeks following a Covid-19 infection, you have to be prepared to take things slowly and manage your expectations on what you can and can't do.
Dr. Erica Spatz, an associate professor of cardiology at the Yale School of Medicine, said a common complaint is that even just going for a walk feels awful. When returning to exercise, "start with five to 10 minutes on a recumbent bicycle or a rower, and add a couple of minutes every week," she suggested.
This "go slow" advice applies to all lingering effects of Covid, including cognition.
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The number of new coronavirus cases in Connecticut continued to fall this week, along with hospitalizations, though Hartford Healthcares COVID-19 expert warned the virus is not going away anytime soon.
There were 3,583 positive cases recorded by the state in the past seven days, less than half of the 7,560 recorded the week before, according to state data, available at data.ct.gov. With 33,085 tests recorded, the states positivity rate is now 10.83%, down from 12.05% on May 26 and 14% on May 19, showing the decline of a wave that began in early April with a highly transmissible variant of omicron.
Hospitalizations also fell, from 379 a week ago to 311 Thursday. Officials note that many of those are incidental cases, in which people were admitted to a hospital for other reasons and then tested positive upon arrival.
Connecticut saw 39 COVID-related deaths in the past week, the data shows. There were 19 deaths recorded last week and an additional 39 the week of May 19. Research has shown that deaths from the virus tend to lag behind an increase in cases.
Omicron continues to be the dominant variant, the state said, with BA.2 accounting for 89% of cases diagnosed this week. Evolving subvariants will continue to drive transmission through the summer with a spike in the fall, Ulysses Wu, MD, chief epidemiologist for Hartford HealthCare, said in a post Thursday on Hartford Healthcares News Hub.
Levels are not going to approach winter levels or last summers delta variant levels, but we also will not approach the lows that we would like to see, Wu said. We will continue to go through waves of swells throughout the early summer at the least, with a likely spike in late fall.
He predicted new surges could come from subvariants BA.4 and BA.5, which were detected in the United States in late March, and seem to evade immunity created by vaccines and previous infection.
With transmission still high, experts recommend people vaccinated or not continue to wear masks indoors and in crowded spaces.
Total vaccine doses distributed: 747,974,855
Patients whove received the first dose: 258,655,540
Patients whove received the second dose: 221,350,544
% of population fully vaccinated (both doses, not including boosters): 66.7%
% tied to Omicron variant: 99.9%
% tied to Other: 0.1%
In a recent study published in Emerging Infectious Diseases, researchers evaluated the increase in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections among university students immediately after returning to their university in September 2020. The students relocated to their universities for the new academic term during the coronavirus disease 2019 (COVID-19) pandemic in England.
In the United Kingdom (UK), university students relocate to their universities in September at the commencement of the new academic term, which coincided with the surge in COVID-19 cases in the country during that period. While some United Kingdom (UK) universities preferred online teaching, some universities required students to be present in person. Unfortunately, immediately after the new academic term started, SARS-CoV-2 outbreaks occurred associated with the universities.
In the present study, researchers evaluated the increase in COVID-19 cases and outbreaks on the return of students to their universities for the new academic term beginning September 2020 during the SARS-CoV-2 pandemic.
SARS-CoV-2-positive students (student case patients) were identified based on contact tracing records and their university attendance. Student case patients residing in university student accommodations were identified by matching their residential addresses with national property databases. SARS-CoV-2-positive individuals were asked about their activities and events within a week before the onset of COVID-19 symptoms/ date of the test, which included data on their attendance in educational settings.
For identifying university attendees among case patients, those with SARS-CoV-2-positive reports were linked to the National Health Service (NHS) test and trace exposure data. Contact tracing and case patient data were linked by the SARS-CoV-2-positive specimen number, date of birth, and the NHS number.
The types of accommodation were identified by matching the case patient address with the Ordnance Survey Address Base Premium database, wherein each address is assigned a unique property reference number (UPRN) which enables mapping case patients to a particular area of residence. Age-specific case rates were compared between towns with universities to those without using the Office for National Statistics (ONS) 2019 midyear estimates. COVID-19 case rates among student case patients and the rest of the population were compared, and the geographic regions with the highest number of cases were determined.
Between 1 September 2020 and 31 December 2020, 1,999,180 COVID-19 cases were reported in England, of which 53,430 (2.7%) were student case patients. After the new academic term began (in September), a rapid increase in student case patients from 0.7% to 7.8% from September to October. The increase in COVID-19 cases was initially driven by cases and SARS-CoV-2 outbreaks in university student accommodations, most pronounced in individuals aged 18 to 23 years (student population), and was two-fold higher in towns with universities.
In the student population, cases increased from 11 COVID-19 cases/100,000 individuals to 99 COVID-19 cases/100,000 individuals between 1 September 2020 and 1 October 2020. During the same period, the COVID-19 case rate among the remaining population of England increased from three to 13 COVID-19 cases/100,000 individuals. At the commencement of the academic term, 60% to 70% of student case patients lived in student accommodations, which dropped to 20% to 30% after mid-November.
The mean ages of student case patients and all case patients were 20 years and 37 years, respectively, and a higher proportion of females among student case patients (57% females vs. 53% males). Most student case patients were reported in Nottingham, Sheffield, Bristol, Manchester, Birmingham, and Leeds. Most student case patients residing in student accommodations were reported in Nottingham, Sheffield, York, Newcastle, and Coventry.
SARS-CoV-2 outbreaks in student accommodations continued for six days compared to two days for other accommodation settings. Outbreaks that involved students showed an upward trend, increasing from 0.7% to 7.3% in September 2020 but declining to 1% by December 2020. A significant reduction in COVID-19 cases was observed in November after the second period of national restrictions in university towns; however, the rates increased in December after the restrictions were lifted.
To summarize, the unprecedented increase in COVID-19 cases among university students after their term began, likely due to the physical and social interactions of students in enclosed spaces during the university fresher week, was reduced by enforcing national COVID-19 restrictions. The study highlights the need for stringent preventive measures to curtail SARS-CoV-2 transmission.
The total number of new cases of COVID-19 in Evanston was 270 for the week ending June 1, 19% lower than the week ending May 26. The number of new cases in the State dropped by 10%. Hospitalizations, though, increased slightly.
This evening, June 2, Evanstons Health and Human Services Department ranked Evanston in the medium community risk level. The Center of Disease Control and Prevention and the Illinois Department of Public Health ranked Cook County, including Chicago, in the high community risk level. Lake, McHenry, DuPage and Will Counties are also in the high community risk level.
Researchers estimate that the actual number of new COVID-19 cases is about six or seven times the number being reported because many people who test positive on tests taken at home are not reporting them. A recent New York City study suggests that the actual number of new cases may be under-reported by a factor of 30.
Wastewater Testing
The Illinois Department of Public Health (IDPH) and the Discovery Partners Institute (DPI) announced today, June 2, that their comprehensive effort to monitor the coronavirus and its variants in wastewater will extend into mid-2023.
The federally funded effort will help public health officials track the prevalence of COVID-19 across Illinois and provide a potential sign of another surge in infections, said the Governors office in a prepared statement. SARS-CoV-2, the virus that causes COVID-19, is detectable in human waste nearly from the onset of infection, while symptoms may not appear for three to five days.
We are very grateful to our federal funding partners for the support that allows us to continue building our capacity to conduct wastewater surveillance in communities throughout the state of Illinois, said IDPH Acting Director Amaal Tokars. This technology holds the promise of serving as a sentinel, early-warning system for the presence of disease as well as new variants of concern.
The Illinois Wastewater Surveillance System is a collaboration among IDPH and scientists from DPI, the University of Illinois Chicago, Northwestern University, Argonne National Laboratory and the University of Illinois Urbana-Champaign. The team has established collection sites at 71 wastewater-treatment facilities in 46 counties in the State. Nearly 200 samples are collected each week, and they are then transported to a UIC microbiology lab for analysis. A subset of samples is also sequenced at Argonne to determine which COVID-19 variants are infecting people at any given time. The results are forwarded to IDPH and can be used to inform public health protocols.
Trends of New Cases in Illinois and Evanston
Illinois: On June 2, the number of new cases in the state was 6,300, down from 6,358 one week ago.
The seven-day average of new cases in Illinois on June 2 was 6,358, down from 5,125 on May 26, a 10% decrease. The chart below shows the trend.
Evanston: Evanston reported there were 44 new COVID-19 cases of Evanston residents on June 1. (Evanston is reporting COVID-19 data with a one-day delay.)
There was a total of 270 new COVID-19 cases of Evanston residents in the week ending June 1, compared to 334 new cases in the week ending May 26, a decrease of 19%.
The chart below shows the trend.
No Evanstonian died due to COVID-19 during the week ending June 1. The number of deaths due to COVID-19 remains at 149.
Cases at D65, ETHS, and NU: It appears that the new cases at the schools continue to account for a significant number of the new cases in Evanston.
School District 65s COVID-19 dashboard reports that for the seven-days ending May 31, a total of 86 students and 23 staff members tested positive for COVID-19.
ETHS reports on its dashboard that in the seven-days ending May 23 (the most recent report for ETHS), 50 students and 13 staff tested positive for COVID-19.
The data does not reflect whether the students and staff contracted the virus while at school.
The latest data reported on NUs website is that between May 20 and May 26 there were 393 new COVID-19 cases of faculty, staff or students. If the cases are of an Evanston resident, they are included in Evanstons data for the relevant period, Ike Ogbo, Director of Evanstons Department of Health and Human Services, told the RoundTable. NU will update its data tomorrow.
Cases Per 100,000
The weekly number of new cases per 100,000 people in Illinois is 255 in the seven days ending June 2.
As of June 1, the weekly number of new cases per 100,000 people in Evanston was 365. As of June 2, the number was 244 for Chicago, and 281 for Suburban Cook County. An accompanying chart shows the trend.
Hospitalizations
Hospitalizations due to COVID-19 have more than doubled in the last seven weeks. They have increased from 517 on April 6 to 1,267 on June 1.
The chart below, prepared by the City of Evanston, shows the trends in hospitalizations due to COVID-19 at the closest three hospitals serving Evanston residents.
Cook County is in the High Risk Level
The CDC and IDPH look at the combination of three metrics to determine whether a community level of risk for COVID-19 is low, medium, or high. They are: 1) the total number of new COVID-19 cases per 100,000 people in the last 7 days; 2) the new COVID-19 hospital admissions per 100,000 in the last 7 days; and 3) the percent of staffed inpatient hospital beds occupied by COVID-19 patients. [1]
The City of Evanston reported this evening, June 2, that Evanston is in the medium risk category. While the number of new COVID-19 cases exceeded the number required to be put in the high risk level, the Citys Health and Human Services Department reported that the number of hospitalizations of Evanston residents was low and the percent of inpatient hospital beds being used for COVID-19 patients was also low.
CDC and IDPH reported, however, that Cook County, including Chicago, is the high risk category.
The CDC and IDPH recommend the following measures for people in areas that are rated at a high community Level for COVID-19 transmission:
At all levels, people can wear a mask based on personal preference, informed by personal level of risk. People with symptoms, a positive test, or exposure to someone with COVID-19 should wear a mask.
FOOTNOTES
1/ CDC recommends the use of three indicators to measure COVID-19 Community Levels: 1) new COVID-19 cases per 100,000 population in the last 7 days; 2) new COVID-19 hospital admissions per 100,000 population in the last 7 days; and 3) the percent of staffed inpatient beds occupied by patients with confirmed COVID-19 (7-day average).
The chart below illustrates how these indicators are combined to determine whether COVID-19 Community Levels are low, medium, or high. The CDC provides many recommendations depending on whether the COVID-19 Community Level is low, medium, or high.
https://www.cdc.gov/coronavirus/2019-ncov/science/science-briefs/indicators-monitoring-community-levels.html
The West Virginia Department of Health and Human Resources (DHHR) reports as of June 2, 2022, there are currently 2,117 active COVID-19 cases statewide. There have been nine deaths reported since the last report, with a total of 6,971 deaths attributed to COVID-19.
DHHR has confirmed the deaths of an 89-year old female from Greenbrier County, a 77-year old male from Greenbrier County, and a 67-year old male from Jefferson County.
Included in the total deaths reported on the dashboard as a result of the Bureau for Public Healths continuing data reconciliation with the official death certificate are a 67-year old female from Putnam County, an 81-year old male from Ohio County, a 27-year old female from Wayne County, a 72-year old male from Monongalia County, a 100-year old female from Mineral County, and a 15-year old female from Raleigh County. These deaths range from January through May 2022, with three deaths occurring in September and December 2021.
We offer our deepest condolences as our state grieves more losses due to COVID-19, said Bill J. Crouch, DHHR Cabinet Secretary. Scheduling a COVID-19 vaccine and booster shot are the most powerful ways to prevent further loss of life due to this devastating disease.
CURRENT ACTIVE CASES PER COUNTY: Barbour (10), Berkeley (156), Boone (20), Braxton (8), Brooke (17), Cabell (106), Calhoun (10), Clay (2), Doddridge (3), Fayette (58), Gilmer (2), Grant (9), Greenbrier (30), Hampshire (20), Hancock (37), Hardy (13), Harrison (91), Jackson (12), Jefferson (106), Kanawha (210), Lewis (35), Lincoln (24), Logan (47), Marion (88), Marshall (29), Mason (41), McDowell (13), Mercer (83), Mineral (32), Mingo (23), Monongalia (125), Monroe (17), Morgan (7), Nicholas (56), Ohio (62), Pendleton (1), Pleasants (4), Pocahontas (3), Preston (22), Putnam (66), Raleigh (97), Randolph (41), Ritchie (8), Roane (25), Summers (7), Taylor (30), Tucker (4), Tyler (4), Upshur (43), Wayne (34), Webster (5), Wetzel (24), Wirt (4), Wood (56), Wyoming (37). To find the cumulative cases per county, please visit coronavirus.wv.gov and look on the Cumulative Summary tab which is sortable by county.
West Virginians ages 5 and older are recommended to get a COVID-19 vaccine booster shot when due. Second booster shots for those age 50 and over who are 4 months or greater from their first booster are recommended, as well as for younger individuals over 12 years old with serious and chronic health conditions that lead to being considered moderately to severely immunocompromised.
Visit the WV COVID-19 Vaccination Due Date Calculator, a free, online tool that helps individuals figure out when they may be due for a COVID-19 shot, making it easier to stay up-to-date on COVID-19 vaccination. To learn more about COVID-19 vaccines, or to find a vaccine site near you, visit vaccinate.wv.gov or call 1-833-734-0965.
To locate free COVID-19 testing near you, please visit https://dhhr.wv.gov/COVID-19/pages/testing.aspx.
