SARS-CoV-2 transmission, vaccination rate and the fate of resistant strains

Vaccines are thought to be the best available solution for controlling the ongoing SARS-CoV-2 pandemic1,2. However, the emergence of vaccine-resistant strains3–6 may come too rapidly for current vaccine developments to alleviate the health, economic and social consequences of the pandemic7,8. To quantify and characterize the risk of such a scenario, we created a SIR-derived model9,10 with initial stochastic dynamics of the vaccine-resistant strain to study the probability of its emergence and establishment. Using parameters realistically resembling SARS-CoV-2 transmission, we model a wave-like pattern of the pandemic and consider the impact of the rate of vaccination and the strength of non-pharmaceutical intervention measures on the probability of emergence of a resistant strain. We found a counterintuitive result that the highest probability for the establishment of the resistant strain comes at a time of reduced non-pharmaceutical intervention measures when most individuals of the population have been vaccinated. Consequently, we show that a period of transmission reduction close to the end of the vaccination campaign can substantially reduce the probability of resistant strain establishment. Our results suggest that policymakers and individuals should consider maintaining non-pharmaceutical interventions7,11,12 throughout the entire vaccination period.

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Rates of SARS-CoV-2 transmission and vaccination impact the fate of vaccine-resistant strains

Scientific Reports ◽

10.1038/s41598-021-95025-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Simon A. Rella ◽

Yuliya A. Kulikova ◽

Emmanouil T. Dermitzakis ◽

Fyodor A. Kondrashov

Keyword(s):

Resistant Strain ◽

Stochastic Dynamics ◽

Vaccination Campaign ◽

Social Consequences ◽

Intervention Measures ◽

Current Vaccine ◽

Transmission Reduction ◽

Resistant Strains ◽

The Impact ◽

Pharmaceutical Interventions

AbstractVaccines are thought to be the best available solution for controlling the ongoing SARS-CoV-2 pandemic. However, the emergence of vaccine-resistant strains may come too rapidly for current vaccine developments to alleviate the health, economic and social consequences of the pandemic. To quantify and characterize the risk of such a scenario, we created a SIR-derived model with initial stochastic dynamics of the vaccine-resistant strain to study the probability of its emergence and establishment. Using parameters realistically resembling SARS-CoV-2 transmission, we model a wave-like pattern of the pandemic and consider the impact of the rate of vaccination and the strength of non-pharmaceutical intervention measures on the probability of emergence of a resistant strain. As expected, we found that a fast rate of vaccination decreases the probability of emergence of a resistant strain. Counterintuitively, when a relaxation of non-pharmaceutical interventions happened at a time when most individuals of the population have already been vaccinated the probability of emergence of a resistant strain was greatly increased. Consequently, we show that a period of transmission reduction close to the end of the vaccination campaign can substantially reduce the probability of resistant strain establishment. Our results suggest that policymakers and individuals should consider maintaining non-pharmaceutical interventions and transmission-reducing behaviours throughout the entire vaccination period.

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Modelling the impact of delaying vaccination against SARS-CoV-2 assuming unlimited vaccine supply

Theoretical Biology and Medical Modelling ◽

10.1186/s12976-021-00143-0 ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Marcos Amaku ◽

Dimas Tadeu Covas ◽

Francisco Antonio Bezerra Coutinho ◽

Raymundo Soares Azevedo ◽

Eduardo Massad

Keyword(s):

Mathematical Model ◽

Vaccination Campaign ◽

Vaccination Rate ◽

Sao Paulo ◽

The State ◽

São Paulo ◽

Health Authorities ◽

The World ◽

The Moment ◽

The Impact

Abstract Background At the moment we have more than 177 million cases and 3.8 million deaths (as of June 2021) around the world and vaccination represents the only hope to control the pandemic. Imperfections in planning vaccine acquisition and difficulties in implementing distribution among the population, however, have hampered the control of the virus so far. Methods We propose a new mathematical model to estimate the impact of vaccination delay against the 2019 coronavirus disease (COVID-19) on the number of cases and deaths due to the disease in Brazil. We apply the model to Brazil as a whole and to the State of Sao Paulo, the most affected by COVID-19 in Brazil. We simulated the model for the populations of the State of Sao Paulo and Brazil as a whole, varying the scenarios related to vaccine efficacy and compliance from the populations. Results The model projects that, in the absence of vaccination, almost 170 thousand deaths and more than 350 thousand deaths will occur by the end of 2021 for Sao Paulo and Brazil, respectively. If in contrast, Sao Paulo and Brazil had enough vaccine supply and so started a vaccination campaign in January with the maximum vaccination rate, compliance and efficacy, they could have averted more than 112 thousand deaths and 127 thousand deaths, respectively. In addition, for each month of delay the number of deaths increases monotonically in a logarithmic fashion, for both the State of Sao Paulo and Brazil as a whole. Conclusions Our model shows that the current delay in the vaccination schedules that is observed in many countries has serious consequences in terms of mortality by the disease and should serve as an alert to health authorities to speed the process up such that the highest number of people to be immunized is reached in the shortest period of time.

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Mobility network reveals the impact of geographic vaccination heterogeneity on COVID-19

10.1101/2021.10.26.21265488 ◽

2021 ◽

Author(s):

Yuan Yuan ◽

Eaman Jahani ◽

Shengjia Zhao ◽

Yong-Yeol Ahn ◽

Alex Pentland

Keyword(s):

Computational Models ◽

Negative Impact ◽

Vaccination Campaign ◽

Vaccination Rate ◽

Control Measures ◽

Vaccine Uptake ◽

Vaccination Rates ◽

The Impact ◽

Hub Effect ◽

The U.S

ABSTRACTMassive vaccination is one of the most effective epidemic control measures. Because one’s vaccination decision is shaped by social processes (e.g., socioeconomic sorting and social contagion), the pattern of vaccine uptake tends to show strong social and geographical heterogeneity, such as urban-rural divide and clustering. Yet, little is known to what extent and how the vaccination heterogeneity affects the course of outbreaks. Here, leveraging the unprecedented availability of data and computational models produced during the COVID-19 pandemic, we investigate two network effects—the “hub effect” (hubs in the mobility network usually have higher vaccination rates) and the “homophily effect” (neighboring places tend to have similar vaccination rates). Applying Bayesian deep learning and fine-grained simulations for the U.S., we show that stronger homophily leads to more infections while a stronger hub effect results in fewer cases. Our simulation estimates that these effects have a combined net negative impact on the outcome, increasing the total cases by approximately 10% in the U.S. Inspired by these results, we propose a vaccination campaign strategy that targets a small number of regions to further improve the vaccination rate, which can reduce the number of cases by 20% by only vaccinating an additional 1% of the population according to our simulations. Our results suggest that we must examine the interplay between vaccination patterns and mobility networks beyond the overall vaccination rate, and that the government may need to shift policy focus from overall vaccination rates to geographical vaccination heterogeneity.

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Mobility network reveals the impact of spatial vaccination heterogeneity on COVID‐19

10.21203/rs.3.rs-1065491/v1 ◽

2021 ◽

Author(s):

Yuan Yuan ◽

Eaman Jahani ◽

Shengjia Zhao ◽

Yong-Yeol Ahn ◽

Alex Pentland

Keyword(s):

Computational Models ◽

Network Effects ◽

Vaccination Campaign ◽

Vaccination Rate ◽

Control Measures ◽

Vaccine Uptake ◽

Vaccination Rates ◽

Fine Grained ◽

Mobility Data ◽

The Impact

Abstract Massive vaccination is one of the most effective epidemic control measures. Because one’s vaccination decision is shaped by social processes (e.g., socioeconomic sorting and social contagion), the pattern of vaccine uptake tends to show strong social and spatial heterogeneity, such as urban-rural divide and clustering. Examining through network perspectives, here we quantify the impact of spatial vaccination heterogeneity on COVID outbreaks and offer policy recommendations on location-based vaccination campaigns. Leveraging fine-grained mobility data and computational models, we investigate two network effects—the “hub effect” (hubs in the mobility network usually have higher vaccination rates) and the “homophily effect” (neighboring places tend to have similar vaccination rates). Applying Bayesian deep learning and fine-grained epidemic simulations, we show a negative effect of homophily and a positive effect of highly vaccinated hubs on reducing COVID-19 case counts; these two effects are estimated to jointly increase the total cases by approximately 10% in the U.S. Moreover, inspired by these results, we propose a vaccination campaign strategy that targets a small number of regions with the largest gain in protective power. Our simulation shows that we can reduce the number of cases by 20% by only vaccinating an additional 1% of the population. Our study suggests that we must examine the interplay between vaccination patterns and mobility networks beyond the overall vaccination rate, and that accurate location-based targeting can be equally if not more important than improving the overall vaccination rate.

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Modelling the Impact of Delaying Vaccination Against SARS-CoV-2 Assuming Unlimited Vaccines Supply

10.21203/rs.3.rs-605245/v1 ◽

2021 ◽

Author(s):

Eduardo Massad ◽

Marcos Amaku ◽

Dimas Tadeu Covas ◽

Francisco Antonio Bezerra Coutinho ◽

Raymundo Soares Azevedo

Keyword(s):

Mathematical Model ◽

Vaccination Campaign ◽

Vaccination Rate ◽

Sao Paulo ◽

The State ◽

São Paulo ◽

Health Authorities ◽

The World ◽

The Moment ◽

The Impact

Abstract BackgroundAt the moment we have more than 109 million cases and 2.4 million deaths around the world and vaccination represents the only hope to control the pandemic. Imperfections in planning vaccine acquisition and difficulties in implementing distribution among the population, however, have hampered the control of the virus so far.MethodsWe propose a new mathematical model to estimate the impact of vaccination delay against the 2019 coronavirus induces disease (COVID-19) on the number of cases and deaths by the disease in Brazil. We apply the model to Brazil as a whole and to the State of Sao Paulo, the most affected by COVID-19 in Brazil. We simulated the model for the populations of the State of Sao Paulo and Brazil as a whole, varying the scenarios related to vaccine efficacy and compliance from the populations.ResultsThe model projects that, in the absence of vaccination, almost 170 thousand deaths and more than 350 thousand deaths until the end of 2021 for Sao Paulo and Brazil, respectively. If in contrast, Sao Paulo and Brazil had enough vaccine supply and so started a vaccination campaign in January with the maximum vaccination rate, compliance and efficacy, they could have averted more than 112 thousand deaths and 127 thousand deaths, respectively. In addition, that for each month of delay the number of deaths increases monotonically in a logarithm fashion, for both the State of Sao Paulo and Brazil as a whole.ConclusionsOur model shows that the current delay in the vaccination schedules that is observed in many countries has serious consequences in terms of mortality by the disease and should serve as an alert to health authorities to speed the process up such that the highest number of people to be immunized is reached in the shortest period of time.

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Modelling the Impact of Delaying Vaccination Against SARS-CoV-2 Assuming Unlimited Vaccines Supply

10.1101/2021.02.22.21252189 ◽

2021 ◽

Author(s):

Marcos Amaku ◽

Dimas Tadeu Covas ◽

Francisco Antonio Bezerra Coutinho ◽

Raymundo Soares Azevedo ◽

Eduardo Massad

Keyword(s):

Mathematical Model ◽

Vaccination Campaign ◽

Vaccination Rate ◽

Sao Paulo ◽

The State ◽

São Paulo ◽

Health Authorities ◽

The World ◽

The Moment ◽

The Impact

AbstractBackgroundAt the moment we have more than 109 million cases and 2.4 million deaths around the world and vaccination represents the only hope to control the pandemic. Imperfections in planning vaccine acquisition and difficulties in implementing distribution among the population, however, have hampered the control of the virus so far.MethodsWe propose a new mathematical model to estimate the impact of vaccination delay against COVID-19 on the number of cases and deaths by the disease in Brazil. We apply the model to Brazil as a whole and to the State of Sao Paulo, the most affected by COVID-19 in Brazil. We simulated the model for the populations of the State of Sao Paulo and Brazil as a whole, varying the scenarios related to vaccine efficacy and compliance from the populations.ResultsThe model projects that, in the absence of vaccination, almost 170 thousand deaths and more than 350 thousand deaths until the end of 2021 for Sao Paulo and Brazil, respectively. If in contrast, Sao Paulo and Brazil had enough vaccine supply and so started a vaccination campaign in January with the maximum vaccination rate, compliance and efficacy, they could have averted more than 112 thousand deaths and 127 thousand deaths, respectively. In addition, that for each month of delay the number of deaths increases monotonically in a logarithm fashion, for both the State of Sao Paulo and Brazil as a whole.ConclusionsOur model shows that the current delay in the vaccination schedules that is observed in many countries has serious consequences in terms of mortality by the disease and should serve as an alert to health authorities to speed the process up such that the highest number of people to be immunized is reached in the shortest period of time.

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Using syndromic measures of mortality to capture the dynamics of COVID-19 in Java, Indonesia, in the context of vaccination rollout

BMC Medicine ◽

10.1186/s12916-021-02016-2 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Bimandra A. Djaafara ◽

Charles Whittaker ◽

Oliver J. Watson ◽

Robert Verity ◽

Nicholas F. Brazeau ◽

...

Keyword(s):

Rural Areas ◽

Vaccination Campaign ◽

Control Measures ◽

Additional Insight ◽

Short Term ◽

If Current ◽

Vaccine Impact ◽

Potential Impact ◽

The Impact ◽

Insight Into

Abstract Background As in many countries, quantifying COVID-19 spread in Indonesia remains challenging due to testing limitations. In Java, non-pharmaceutical interventions (NPIs) were implemented throughout 2020. However, as a vaccination campaign launches, cases and deaths are rising across the island. Methods We used modelling to explore the extent to which data on burials in Jakarta using strict COVID-19 protocols (C19P) provide additional insight into the transmissibility of the disease, epidemic trajectory, and the impact of NPIs. We assess how implementation of NPIs in early 2021 will shape the epidemic during the period of likely vaccine rollout. Results C19P burial data in Jakarta suggest a death toll approximately 3.3 times higher than reported. Transmission estimates using these data suggest earlier, larger, and more sustained impact of NPIs. Measures to reduce sub-national spread, particularly during Ramadan, substantially mitigated spread to more vulnerable rural areas. Given current trajectory, daily cases and deaths are likely to increase in most regions as the vaccine is rolled out. Transmission may peak in early 2021 in Jakarta if current levels of control are maintained. However, relaxation of control measures is likely to lead to a subsequent resurgence in the absence of an effective vaccination campaign. Conclusions Syndromic measures of mortality provide a more complete picture of COVID-19 severity upon which to base decision-making. The high potential impact of the vaccine in Java is attributable to reductions in transmission to date and dependent on these being maintained. Increases in control in the relatively short-term will likely yield large, synergistic increases in vaccine impact.

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Correlates of Improved Influenza Vaccination of Healthcare Personnel: A Survey of Hospitals in Louisiana

Infection Control and Hospital Epidemiology ◽

10.1086/670992 ◽

2013 ◽

Vol 34 (7) ◽

pp. 723-729 ◽

Cited By ~ 6

Author(s):

Kayla L. Fricke ◽

Mariella M. Gastañaduy ◽

Renee Klos ◽

Rodolfo E. Bégué

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Influenza Vaccination ◽

Vaccination Campaign ◽

Vaccination Rate ◽

Healthcare Personnel ◽

Patient Contact ◽

Hospital Type ◽

Vaccination Rates ◽

Item Questionnaire

Objective.To describe practices for influenza vaccination of healthcare personnel (HCP) with emphasis on correlates of increased vaccination rates.Design.Survey.Participants.Volunteer sample of hospitals in Louisiana.Methods.All hospitals in Louisiana were invited to participate. A 17-item questionnaire inquired about the hospital type, patients served, characteristics of the vaccination campaign, and the resulting vaccination rate.Results.Of 254 hospitals, 153 (60%) participated and were included in the 124 responses that were received. Most programs (64%) required that HCP either receive the vaccine or sign a declination form, and the rest were exclusively voluntary (36%); no program made vaccination a condition of employment. The median vaccination rate was 67%, and the vaccination rate was higher among hospitals that were accredited by the Joint Commission; provided acute care; served children, pregnant women, oncology patients, or intensive care unit patients; required a signed declination form; or imposed consequences for unvaccinated HCP (the most common of which was to require that a mask be worn on patient contact). Hospitals that provided free vaccine, made vaccine widely available, advertised the program extensively, required a declination form, and imposed consequences had the highest vaccination rates (median, 86%; range, 81%–91%).Conclusions.The rate of influenza vaccination of HCP remains low among the hospitals surveyed. Recommended practices may not be enough to reach 90% vaccination rates unless a signed declination requirement and consequences are implemented. Wearing a mask is a strong consequence. Demanding influenza vaccination as a condition of employment was not reported as a practice by the participating hospitals.

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Influenza With an Infiltrate: Investigating the New Community-Acquired Pneumonia Guidelines

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.884 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s302-s302

Author(s):

Amanda Barner ◽

Lou Ann Bruno-Murtha

Keyword(s):

Demographic Data ◽

Retrospective Chart Review ◽

Vaccination Rate ◽

Community Acquired Pneumonia ◽

Teaching Hospitals ◽

Antibiotic Prescribing ◽

Supporting Evidence ◽

Radiographic Findings ◽

Significant Difference ◽

The Impact

Background: The Infectious Diseases Society of America released updated community-acquired pneumonia (CAP) guidelines in October 2019. One of the recommendations, with a low quality of supporting evidence, is the standard administration of antibiotics in adult patients with influenza and radiographic evidence of pneumonia. Procalcitonin (PCT) is not endorsed as a strategy to withhold antibiotic therapy, but it could be used to de-escalate appropriate patients after 48–72 hours. Radiographic findings are not indicative of the etiology of pneumonia. Prescribing antibiotics for all influenza-positive patients with an infiltrate has significant implications for stewardship. Therefore, we reviewed hospitalized, influenza-positive patients at our institution during the 2018–2019 season, and we sought to assess the impact of an abnormal chest x-ray (CXR) and PCT on antibiotic prescribing and outcomes. Methods: We conducted a retrospective chart review of all influenza-positive admissions at 2 urban, community-based, teaching hospitals. Demographic data, vaccination status, PCT levels, CXR findings, and treatment regimens were reviewed. The primary outcome was the difference in receipt of antibiotics between patients with a negative (<0.25 ng/mL) and positive PCT. Secondary outcomes included the impact of CXR result on antibiotic prescribing, duration, 30-day readmission, and 90-day mortality. Results: We reviewed the medical records of 117 patients; 43 (36.7%) received antibiotics. The vaccination rate was 36.7%. Also, 11% of patients required intensive care unit (ICU) admission and 84% received antibiotics. Moreover, 109 patients had a CXR: 61 (55.9%) were negative, 29 (26.6%) indeterminate, and 19 (17.4%) positive per radiologist interpretation. Patients with a positive PCT (OR, 12.7; 95% CI, 3.43–60.98; P < .0007) and an abnormal CXR (OR, 7.4; 95% CI, 2.9–20.1; P = .000003) were more likely to receive antibiotics. There was no significant difference in 30-day readmission (11.6% vs 13.5%; OR, 0.89; 95% CI, 0.21–3.08; P = 1) and 90-day mortality (11.6% vs 5.4%; OR, 2.37; 95% CI, 0.48–12.75; P = .28) between those that received antibiotics and those that did not, respectively. Furthermore, 30 patients (62.5%) with an abnormal CXR received antibiotics and 21 (43.7%) had negative PCT. There was no difference in 30-day readmission or 90-day mortality between those that did and did not receive antibiotics. Conclusions: Utilization of PCT allowed selective prescribing of antibiotics without impacting readmission or mortality. Antibiotics should be initiated for critically ill patients and based on clinical judgement, rather than for all influenza-positive patients with CXR abnormalities.Funding: NoneDisclosures: None

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The Effect of Vaccination Rates on the Infection of COVID-19 under the Vaccination Rate below the Herd Immunity Threshold

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18147491 ◽

2021 ◽

Vol 18 (14) ◽

pp. 7491

Author(s):

Yi-Tui Chen

Keyword(s):

Infection Rate ◽

Herd Immunity ◽

The United States ◽

Vaccination Rate ◽

Infection Rates ◽

Vaccination Rates ◽

The United Kingdom ◽

The World ◽

Almost All ◽

The Impact

Although vaccination is carried out worldwide, the vaccination rate varies greatly. As of 24 May 2021, in some countries, the proportion of the population fully vaccinated against COVID-19 has exceeded 50%, but in many countries, this proportion is still very low, less than 1%. This article aims to explore the impact of vaccination on the spread of the COVID-19 pandemic. As the herd immunity of almost all countries in the world has not been reached, several countries were selected as sample cases by employing the following criteria: more than 60 vaccine doses per 100 people and a population of more than one million people. In the end, a total of eight countries/regions were selected, including Israel, the UAE, Chile, the United Kingdom, the United States, Hungary, and Qatar. The results find that vaccination has a major impact on reducing infection rates in all countries. However, the infection rate after vaccination showed two trends. One is an inverted U-shaped trend, and the other is an L-shaped trend. For those countries with an inverted U-shaped trend, the infection rate begins to decline when the vaccination rate reaches 1.46–50.91 doses per 100 people.

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