Benefits of near-universal vaccination and treatment access to manage COVID-19 burden in the United States.

BACKGROUND: As we continue the fourth year of the COVID-19 epidemic, SARS-CoV-2 infections still cause high morbidity and mortality in the United States. During 2020-2022, COVID-19 was one of the leading causes of death in the United States and by far the leading cause among infectious diseases. Vaccination uptake remains low despite this being an effective burden reducing intervention. The development of COVID-19 therapeutics provides hope for mitigating severe clinical outcomes. This modeling study examines combined strategies of vaccination and treatment to reduce the burden of COVID-19 epidemics over the next decade. METHODS: We use a validated mathematical model to evaluate the reduction of incident cases, hospitalized cases, and deaths in the United States through 2033 under various levels of vaccination and treatment coverage. We assume that future seasonal transmission patterns for COVID-19 will be similar to those of influenza virus and account for the waning of infection-induced immunity and vaccine-induced immunity in a future with stable COVID-19 dynamics. Due to uncertainty in the duration of immunity following vaccination or infection, we consider three exponentially distributed waning rates, with means of 365 days (1 year), 548 days (1.5 years), and 730 days (2 years). We also consider treatment failure, including rebound frequency, as a possible treatment outcome. RESULTS: As expected, universal vaccination is projected to eliminate transmission and mortality. Under current treatment coverage (13.7%) and vaccination coverage (49%), averages of 81,000-164,600 annual reported deaths, depending on duration of immunity, are expected by the end of this decade. Annual mortality in the United States can be reduced below 50,000 per year with 52-80% annual vaccination coverage and below 10,000 annual deaths with 59-83% annual vaccination coverage, depending on duration of immunity. Universal treatment reduces hospitalizations by 88.6% and deaths by 93.1% under current vaccination coverage. A reduction in vaccination coverage requires a comparatively larger increase in treatment coverage in order for hospitalization and mortality levels to remain unchanged. CONCLUSIONS: Adopting universal vaccination and universal treatment goals in the United States will likely lead to a COVID-19 mortality burden below 50,000 deaths per year, a burden comparable to that of influenza virus.

Optimal SARS-CoV-2 vaccine allocation using real-time attack-rate estimates in Rhode Island and Massachusetts.

BACKGROUND: When three SARS-CoV-2 vaccines came to market in Europe and North America in the winter of 2020-2021, distribution networks were in a race against a major epidemiological wave of SARS-CoV-2 that began in autumn 2020. Rapid and optimized vaccine allocation was critical during this time. With 95% efficacy reported for two of the vaccines, near-term public health needs likely require that distribution is prioritized to the elderly, health care workers, teachers, essential workers, and individuals with comorbidities putting them at risk of severe clinical progression. METHODS: We evaluate various age-based vaccine distributions using a validated mathematical model based on current epidemic trends in Rhode Island and Massachusetts. We allow for varying waning efficacy of vaccine-induced immunity, as this has not yet been measured. We account for the fact that known COVID-positive cases may not have been included in the first round of vaccination. And, we account for age-specific immune patterns in both states at the time of the start of the vaccination program. Our analysis assumes that health systems during winter 2020-2021 had equal staffing and capacity to previous phases of the SARS-CoV-2 epidemic; we do not consider the effects of understaffed hospitals or unvaccinated medical staff. RESULTS: We find that allocating a substantial proportion (>75%) of vaccine supply to individuals over the age of 70 is optimal in terms of reducing total cumulative deaths through mid-2021. This result is robust to different profiles of waning vaccine efficacy and several different assumptions on age mixing during and after lockdown periods. As we do not explicitly model other high-mortality groups, our results on vaccine allocation apply to all groups at high risk of mortality if infected. A median of 327 to 340 deaths can be avoided in Rhode Island (3444 to 3647 in Massachusetts) by optimizing vaccine allocation and vaccinating the elderly first. The vaccination campaigns are expected to save a median of 639 to 664 lives in Rhode Island and 6278 to 6618 lives in Massachusetts in the first half of 2021 when compared to a scenario with no vaccine. A policy of vaccinating only seronegative individuals avoids redundancy in vaccine use on individuals that may already be immune, and would result in 0.5% to 1% reductions in cumulative hospitalizations and deaths by mid-2021. CONCLUSIONS: Assuming high vaccination coverage (>28%) and no major changes in distancing, masking, gathering size, hygiene guidelines, and virus transmissibility between 1 January 2021 and 1 July 2021 a combination of vaccination and population immunity may lead to low or near-zero transmission levels by the second quarter of 2021.

Towards malaria elimination in Savannakhet, Lao PDR: mathematical modelling driven strategy design.

BACKGROUND: The number of Plasmodium falciparum malaria cases around the world has decreased substantially over the last 15 years, but with the spread of resistance against anti-malarial drugs and insecticides, this decline may not continue. There is an urgent need to consider alternative, accelerated strategies to eliminate malaria in countries like Lao PDR, where there are a few remaining endemic areas. A deterministic compartmental modelling tool was used to develop an integrated strategy for P. falciparum elimination in the Savannakhet province of Lao PDR. The model was designed to include key aspects of malaria transmission and integrated control measures, along with a user-friendly interface. RESULTS: Universal coverage was the foundation of the integrated strategy, which took the form of the deployment of community health workers who provided universal access to early diagnosis, treatment and long-lasting insecticidal nets. Acceleration was included as the deployment of three monthly rounds of mass drug administration targeted towards high prevalence villages, with the addition of three monthly doses of the RTS,S vaccine delivered en masse to the same high prevalence sub-population. A booster dose of vaccine was added 1 year later. The surveillance-as-intervention component of the package involved the screening and treatment of individuals entering the simulated population. CONCLUSIONS: In this modelling approach, the sequential introduction of a series of five available interventions in an integrated strategy was predicted to be sufficient to stop malaria transmission within a 3-year period. These interventions comprised universal access to early diagnosis and adequate treatment, improved access to long-lasting insecticidal nets, three monthly rounds of mass drug administration together with RTS,S vaccination followed by a booster dose of vaccine, and screening and treatment of imported cases.

Assessing emergence risk of double-resistant and triple-resistant genotypes of Plasmodium falciparum.

Delaying and slowing antimalarial drug resistance evolution is a priority for malaria-endemic countries. Until novel therapies become available, the mainstay of antimalarial treatment will continue to be artemisinin-based combination therapy (ACT). Deployment of different ACTs can be optimized to minimize evolutionary pressure for drug resistance by deploying them as a set of co-equal multiple first-line therapies (MFT) rather than rotating therapies in and out of use. Here, we consider one potential detriment of MFT policies, namely, that the simultaneous deployment of multiple ACTs could drive the evolution of different resistance alleles concurrently and that these resistance alleles could then be brought together by recombination into double-resistant or triple-resistant parasites. Using an individual-based model, we compare MFT and cycling policies in malaria transmission settings ranging from 0.1% to 50% prevalence. We define a total risk measure for multi-drug resistance (MDR) by summing the area under the genotype-frequency curves (AUC) of double- and triple-resistant genotypes. When prevalence ≥ 1%, total MDR risk ranges from statistically similar to 80% lower under MFT policies than under cycling policies, irrespective of whether resistance is imported or emerges de novo. At 0.1% prevalence, there is little statistical difference in MDR risk between MFT and cycling.

Role of seasonal importation and genetic drift on selection for drug-resistant genotypes of Plasmodium falciparum in high-transmission settings.

Historically Plasmodium falciparum has followed a pattern of drug resistance first appearing in low-transmission settings before spreading to high-transmission settings. Several features of low-transmission regions are hypothesized as explanations: higher chance of symptoms and treatment seeking, better treatment access, less within-host competition among clones and lower rates of recombination. Here, we test whether importation of drug-resistant parasites is more likely to lead to successful emergence and establishment in low-transmission or high-transmission periods of the same epidemiological setting, using a spatial, individual-based stochastic model of malaria and drug-resistance evolution calibrated for Burkina Faso. Upon controlling for the timing of importation of drug-resistant genotypes and examination of key model variables, we found that drug-resistant genotypes imported during the low-transmission season were (i) more susceptible to stochastic extinction due to the action of genetic drift, and (ii) more likely to lead to establishment of drug resistance when parasites are able to survive early stochastic loss due to drift. This implies that rare importation events are more likely to lead to establishment if they occur during a high-transmission season, but that constant importation (e.g. neighbouring countries with high levels of resistance) may produce a greater risk during low-transmission periods.

Global risk of selection and spread of Plasmodium falciparum histidine-rich protein 2 and 3 gene deletions.

In the thirteen years since the first report of pfhrp2-deleted parasites in 2010, the World Health Organization (WHO) has found that 40 of 47 countries surveyed worldwide have reported pfhrp2/3 gene deletions. Due to a high prevalence of pfhrp2/3 deletions causing false-negative HRP2 RDTs, in the last five years, Eritrea, Djibouti and Ethiopia have switched or started switching to using alternative RDTs, that target pan-specific-pLDH or P. falciparum specific-pLDH alone of in combination with HRP2. However, manufacturing of alternative RDTs has not been brought to scale and there are no WHO prequalified combination tests that use Pf-pLDH instead of HRP2 for P. falciparum detection. For these reasons, the continued spread of pfhrp2/3 deletions represents a growing public health crisis that threatens efforts to control and eliminate P. falciparum malaria. National malaria control programmes, their implementing partners and test developers desperately seek pfhrp2/3 deletion data that can inform their immediate and future resource allocation. In response, we use a mathematical modelling approach to evaluate the global risk posed by pfhrp2/3 deletions and explore scenarios for how deletions will continue to spread in Africa. We incorporate current best estimates of the prevalence of pfhrp2/3 deletions and conduct a literature review to estimate model parameters known to impact the selection of pfhrp2/3 deletions for each malaria endemic country. We identify 20 countries worldwide to prioritise for surveillance and future deployment of alternative RDT, based on quickly selecting for pfhrp2/3 deletions once established. In scenarios designed to explore the continued spread of deletions in Africa, we identify 10 high threat countries that are most at risk of deletions both spreading to and subsequently being rapidly selected for. If HRP2-based RDTs continue to be relied on for malaria case management, we predict that the major route for pfhrp2 deletions to spread is south out from the current hotspot in the Horn of Africa, moving through East Africa over the next 20 years. We explore the variation in modelled timelines through an extensive parameter sensitivity analysis and despite wide uncertainties, we identify three countries that have not yet switched RDTs (Senegal, Zambia and Kenya) that are robustly identified as high risk for pfhrp2/3 deletions. These results provide a refined and updated prediction model for the emergence of pfhrp2/3 deletions in an effort to help guide pfhrp2/3 policy and prioritise future surveillance efforts and innovation.

Benefits of near-universal vaccination and treatment access to manage COVID-19 burden in the United States.

Background: As we enter the fourth year of the COVID-19 pandemic, SARS-CoV-2 infections still cause high morbidity and mortality in the United States. During 2020-2022, COVID-19 was one of the leading causes of death in the United States and by far the leading cause among infectious diseases. Vaccination uptake remains low despite this being an effective burden reducing intervention. The development of COVID-19 therapeutics provides hope for mitigating severe clinical outcomes. This modeling study examines combined strategies of vaccination and treatment to reduce the burden of COVID-19 epidemics over the next decade. Methods: We use a validated mathematical model to evaluate the reduction of incident cases, hospitalized cases, and deaths in the United States through 2033 under various levels of vaccination and treatment coverage. We assume that future seasonal transmission patterns for COVID-19 will be similar to those of influenza virus. We account for the waning of infection-induced immunity and vaccine-induced immunity in a future with stable COVID-19 dynamics. Due to uncertainty in the duration of immunity following vaccination or infection, we consider two exponentially-distributed waning rates, with means of 365 days (one year) and 548 days (1.5 years). We also consider treatment failure, including rebound frequency, as a possible treatment outcome. Results: As expected, universal vaccination is projected to eliminate transmission and mortality. Under current treatment coverage (13.7%) and vaccination coverage (49%), averages of 89,000 annual deaths (548-day waning) and 120,000 annual deaths (365-day waning) are expected by the end of this decade. Annual mortality in the United States can be reduced below 50,000 per year with >81% annual vaccination coverage, and below 10,000 annual deaths with >84% annual vaccination coverage. Universal treatment reduces hospitalizations by 88% and deaths by 93% under current vaccination coverage. A reduction in vaccination coverage requires a comparatively larger increase in treatment coverage in order for hospitalization and mortality levels to remain unchanged. Conclusions: Adopting universal vaccination and universal treatment goals in the United States will likely lead to a COVID-19 mortality burden below 50,000 deaths per year, a burden comparable to that of influenza virus.

Antimalarial mass drug administration in large populations and the evolution of drug resistance.

Mass drug administration (MDA) with antimalarials has been shown to reduce prevalence and interrupt transmission in small populations, in populations with reliable access to antimalarial drugs, and in populations where sustained improvements in diagnosis and treatment are possible. In addition, when MDA is effective it eliminates both drug-resistant parasites and drug-sensitive parasites, which has the long-term benefit of extending the useful therapeutic life of first-line therapies for all populations, not just the focal population where MDA was carried out. However, in order to plan elimination measures effectively, it is necessary to characterize the conditions under which failed MDA could exacerbate resistance. We use an individual-based stochastic model of Plasmodium falciparum transmission to evaluate this risk for MDA using dihydroartemisinin-piperaquine (DHA-PPQ), in populations where access to antimalarial treatments may not be uniformly high and where re-importation of drug-resistant parasites may be common. We find that artemisinin-resistance evolution at the kelch13 locus can be accelerated by MDA when all three of the following conditions are met: (1) strong genetic bottlenecking that falls short of elimination, (2) re-importation of artemisinin-resistant genotypes, and (3) continued selection pressure during routine case management post-MDA. Accelerated resistance levels are not immediate but follow the rebound of malaria cases post-MDA, if this is allowed to occur. Crucially, resistance is driven by the selection pressure during routine case management post-MDA and not the selection pressure exerted during the MDA itself. Second, we find that increasing treatment coverage post-MDA increases the probability of local elimination in low-transmission regions (prevalence < 2%) in scenarios with both low and high levels of drug-resistance importation. This emphasizes the importance of planning for and supporting high coverage of diagnosis and treatment post-MDA.

Preventing antimalarial drug resistance with triple artemisinin-based combination therapies.

Increasing levels of artemisinin and partner drug resistance threaten malaria control and elimination globally. Triple artemisinin-based combination therapies (TACTs) which combine artemisinin derivatives with two partner drugs are efficacious and well tolerated in clinical trials, including in areas of multidrug-resistant malaria. Whether early TACT adoption could delay the emergence and spread of antimalarial drug resistance is a question of vital importance. Using two independent individual-based models of Plasmodium falciparum epidemiology and evolution, we evaluated whether introduction of either artesunate-mefloquine-piperaquine or artemether-lumefantrine-amodiaquine resulted in lower long-term artemisinin-resistance levels and treatment failure rates compared with continued ACT use. We show that introduction of TACTs could significantly delay the emergence and spread of artemisinin resistance and treatment failure, extending the useful therapeutic life of current antimalarial drugs, and improving the chances of malaria elimination. We conclude that immediate introduction of TACTs should be considered by policy makers in areas of emerging artemisinin resistance.

Role of Seasonal Importation and Random Genetic Drift on Selection for Drug-Resistant Genotypes of Plasmodium falciparum in High Transmission Settings.

Historically Plasmodium falciparum has followed a pattern of drug resistance first appearing in low transmission settings before spreading to high transmission settings. Several features of low-transmission regions are hypothesized as explanations: higher chance of symptoms and treatment seeking, better treatment access, less within-host competition among clones, and lower rates of recombination. Here, we test whether importation of drug-resistant parasites is more likely to lead to successful emergence and establishment in low-transmission or high-transmission periods of the same epidemiological setting, using a spatial, individual-based stochastic model of malaria and drug-resistance evolution calibrated for Burkina Faso. Upon controlling for the timing of importation of drug-resistant genotypes and examination of key model variables, we found that drug-resistant genotypes imported during the low transmission season were, (1) more susceptible to stochastic extinction due to the action of random genetic drift, and (2) more likely to lead to establishment of drug resistance when parasites are able to survive early stochastic loss due to drift. This implies that rare importation events are more likely to lead to establishment if they occur during a high-transmission season, but that constant importation (e.g., neighboring countries with high levels of resistance) may produce a greater risk during low-transmission periods.

Modeling policy interventions for slowing the spread of artemisinin-resistant pfkelch R561H mutations in Rwanda.

Artemisinin combination therapies (ACTs) are highly effective at treating uncomplicated Plasmodium falciparum malaria, but the emergence of the new pfkelch13 R561H mutation in Rwanda, associated with delayed parasite clearance, suggests that interventions are needed to slow its spread. Using a Rwanda-specific spatial calibration of an individual-based malaria model, we evaluate 26 strategies aimed at minimizing treatment failures and delaying the spread of R561H after 3, 5 and 10 years. Lengthening ACT courses and deploying multiple first-line therapies (MFTs) reduced treatment failures after 5 years when compared to the current approach of a 3-d course of artemether-lumefantrine. The best among these options (an MFT policy) resulted in median treatment failure counts that were 49% lower and a median R561H allele frequency that was 0.15 lower than under baseline. New approaches to resistance management, such as triple ACTs or sequential courses of two different ACTs, were projected to have a larger impact than longer ACT courses or MFT; these were associated with median treatment failure counts in 5 years that were 81-92% lower than the current approach. A policy response to currently circulating artemisinin-resistant genotypes in Africa is urgently needed to prevent a population-wide rise in treatment failures.

Long-term effects of increased adoption of artemisinin combination therapies in Burkina Faso.

Artemisinin combination therapies (ACTs) are the WHO-recommended first-line therapies for uncomplicated Plasmodium falciparum malaria. The emergence and spread of artemisinin-resistant genotypes is a major global public health concern due to the increased rate of treatment failures that result. This is particularly germane for WHO designated 'high burden to high impact' (HBHI) countries, such as Burkina Faso, where there is increased emphasis on improving guidance, strategy, and coordination of local malaria response in an effort to reduce the prevalence of P. falciparum malaria. To explore how the increased adoption of ACTs may affect the HBHI malaria setting of Burkina Faso, we added spatial structure to a validated individual-based stochastic model of P. falciparum transmission and evaluated the long-term effects of increased ACT use. We explored how de novo emergence of artemisinin-resistant genotypes, such as pfkelch13 580Y, may occur under scenarios in which private-market drugs are eliminated or multiple first-line therapies (MFT) are deployed. We found that elimination of private market drugs would result in lower treatment failures rates (between 11.98% and 12.90%) when compared to the status quo (13.11%). However, scenarios incorporating MFT with equal deployment of artemether-lumefantrine (AL) and dihydroartemisinin-piperaquine (DHA-PPQ) may accelerate near-term drug resistance (580Y frequency ranging between 0.62 to 0.84 in model year 2038) and treatment failure rates (26.69% to 34.00% in 2038), due to early failure and substantially reduced treatment efficacy resulting from piperaquine-resistant genotypes. A rebalanced MFT approach (90% AL, 10% DHA-PPQ) results in approximately equal long-term outcomes to using AL alone but may be difficult to implement in practice.

Pre-existing partner-drug resistance to artemisinin combination therapies facilitates the emergence and spread of artemisinin resistance: a consensus modelling study.

BACKGROUND: Artemisinin-resistant genotypes of Plasmodium falciparum have now emerged a minimum of six times on three continents despite recommendations that all artemisinins be deployed as artemisinin combination therapies (ACTs). Widespread resistance to the non-artemisinin partner drugs in ACTs has the potential to limit the clinical and resistance benefits provided by combination therapy. We aimed to model and evaluate the long-term effects of high levels of partner-drug resistance on the early emergence of artemisinin-resistant genotypes. METHODS: Using a consensus modelling approach, we used three individual-based mathematical models of Plasmodium falciparum transmission to evaluate the effects of pre-existing partner-drug resistance and ACT deployment on the evolution of artemisinin resistance. Each model simulates 100 000 individuals in a particular transmission setting (malaria prevalence of 1%, 5%, 10%, or 20%) with a daily time step that updates individuals' infection status, treatment status, immunity, genotype-specific parasite densities, and clinical state. We modelled varying access to antimalarial drugs if febrile (coverage of 20%, 40%, or 60%) with one primary ACT used as first-line therapy: dihydroartemisinin-piperaquine (DHA-PPQ), artesunate-amodiaquine (ASAQ), or artemether-lumefantrine (AL). The primary outcome was time until 0·25 580Y allele frequency for artemisinin resistance (the establishment time). FINDINGS: Higher frequencies of pre-existing partner-drug resistant genotypes lead to earlier establishment of artemisinin resistance. Across all models, a 10-fold increase in the frequency of partner-drug resistance genotypes on average corresponded to loss of artemisinin efficacy 2-12 years earlier. Most reductions in time to artemisinin resistance establishment were observed after an increase in frequency of the partner-drug resistance genotype from 0·0 to 0·10. INTERPRETATION: Partner-drug resistance in ACTs facilitates the early emergence of artemisinin resistance and is a major public health concern. Higher-grade partner-drug resistance has the largest effect, with piperaquine resistance accelerating the early emergence of artemisinin-resistant alleles the most. Continued investment in molecular surveillance of partner-drug resistant genotypes to guide choice of first-line ACT is paramount. FUNDING: Schmidt Science Fellowship in partnership with the Rhodes Trust; Bill & Melinda Gates Foundation; Wellcome Trust.

SARS-CoV-2 Attack Rate and Population Immunity in Southern New England, March 2020 to May 2021.

Importance: In emergency epidemic and pandemic settings, public health agencies need to be able to measure the population-level attack rate, defined as the total percentage of the population infected thus far. During vaccination campaigns in such settings, public health agencies need to be able to assess how much the vaccination campaign is contributing to population immunity; specifically, the proportion of vaccines being administered to individuals who are already seropositive must be estimated. Objective: To estimate population-level immunity to SARS-CoV-2 through May 31, 2021, in Rhode Island, Massachusetts, and Connecticut. Design, Setting, and Participants: This observational case series assessed cases, hospitalizations, intensive care unit occupancy, ventilator occupancy, and deaths from March 1, 2020, to May 31, 2021, in Rhode Island, Massachusetts, and Connecticut. Data were analyzed from July 2021 to November 2021. Exposures: COVID-19-positive test result reported to state department of health. Main Outcomes and Measures: The main outcomes were statistical estimates, from a bayesian inference framework, of the percentage of individuals as of May 31, 2021, who were (1) previously infected and vaccinated, (2) previously uninfected and vaccinated, and (3) previously infected but not vaccinated. Results: At the state level, there were a total of 1 160 435 confirmed COVID-19 cases in Rhode Island, Massachusetts, and Connecticut. The median age among individuals with confirmed COVID-19 was 38 years. In autumn 2020, SARS-CoV-2 population immunity (equal to the attack rate at that point) in these states was less than 15%, setting the stage for a large epidemic wave during winter 2020 to 2021. Population immunity estimates for May 31, 2021, were 73.4% (95% credible interval [CrI], 72.9%-74.1%) for Rhode Island, 64.1% (95% CrI, 64.0%-64.4%) for Connecticut, and 66.3% (95% CrI, 65.9%-66.9%) for Massachusetts, indicating that more than 33% of residents in these states were fully susceptible to infection when the Delta variant began spreading in July 2021. Despite high vaccine coverage in these states, population immunity in summer 2021 was lower than planned owing to an estimated 34.1% (95% CrI, 32.9%-35.2%) of vaccines in Rhode Island, 24.6% (95% CrI, 24.3%-25.1%) of vaccines in Connecticut, and 27.6% (95% CrI, 26.8%-28.6%) of vaccines in Massachusetts being distributed to individuals who were already seropositive. Conclusions and Relevance: These findings suggest that future emergency-setting vaccination planning may have to prioritize high vaccine coverage over optimized vaccine distribution to ensure that sufficient levels of population immunity are reached during the course of an ongoing epidemic or pandemic.

SARS-CoV-2 epidemic after social and economic reopening in three U.S. states reveals shifts in age structure and clinical characteristics.

State-level reopenings in late spring 2020 facilitated the resurgence of severe acute respiratory syndrome coronavirus 2 transmission. Here, we analyze age-structured case, hospitalization, and death time series from three states-Rhode Island, Massachusetts, and Pennsylvania-that had successful reopenings in May 2020 without summer waves of infection. Using 11 daily data streams, we show that from spring to summer, the epidemic shifted from an older to a younger age profile and that elderly individuals were less able to reduce contacts during the lockdown period when compared to younger individuals. Clinical case management improved from spring to summer, resulting in fewer critical care admissions and lower infection fatality rate. Attack rate estimates through 31 August 2020 are 6.2% [95% credible interval (CI), 5.7 to 6.8%] of the total population infected for Rhode Island, 6.7% (95% CI, 5.4 to 7.6%) in Massachusetts, and 2.7% (95% CI, 2.5 to 3.1%) in Pennsylvania.

Optimal SARS-CoV-2 vaccine allocation using real-time seroprevalence estimates in Rhode Island and Massachusetts.

As three SARS-CoV-2 vaccines come to market in Europe and North America in the winter of 2020-2021, distribution networks will be in a race against a major epidemiological wave of SARS-CoV-2 that began in autumn 2020. Rapid and optimized vaccine allocation is critical during this time. With 95% efficacy reported for two of the vaccines, near-term public health needs require that distribution is prioritized to the elderly, health-care workers, teachers, essential workers, and individuals with co-morbidities putting them at risk of severe clinical progression. Here, we evaluate various age-based vaccine distributions using a validated mathematical model based on current epidemic trends in Rhode Island and Massachusetts. We allow for varying waning efficacy of vaccine-induced immunity, as this has not yet been measured. We account for the fact that known COVID-positive cases may not be included in the first round of vaccination. And, we account for current age-specific immune patterns in both states. We find that allocating a substantial proportion ( > 75%) of vaccine supply to individuals over the age of 70 is optimal in terms of reducing total cumulative deaths through mid-2021. As we do not explicitly model other high mortality groups, this result on vaccine allocation applies to all groups at high risk of mortality if infected. Our analysis confirms that for an easily transmissible respiratory virus, allocating a large majority of vaccinations to groups with the highest mortality risk is optimal. Our analysis assumes that health systems during winter 2020-2021 have equal staffing and capacity to previous phases of the SARS-CoV-2 epidemic; we do not consider the effects of understaffed hospitals or unvaccinated medical staff. Vaccinating only seronegative individuals avoids redundancy in vaccine use on individuals that may already be immune, and will result in 1% to 2% reductions in cumulative hospitalizations and deaths by mid-2021. Assuming high vaccination coverage ( > 28%) and no major relaxations in distancing, masking, gathering size, or hygiene guidelines between now and spring 2021, our model predicts that a combination of vaccination and population immunity will lead to low or near-zero transmission levels by the second quarter of 2021.

SARS-CoV-2 attack rate and population immunity in southern New England, March 2020 - May 2021.

Estimating an infectious disease attack rate requires inference on the number of reported symptomatic cases of a disease, the number of unreported symptomatic cases, and the number of asymptomatic infections. Population-level immunity can then be estimated as the attack rate plus the number of vaccine recipients who had not been previously infected; this requires an estimate of the fraction of vaccines that were distributed to seropositive individuals. To estimate attack rates and population immunity in southern New England, we fit a validated dynamic epidemiological model to case, clinical, and death data streams reported by Rhode Island, Massachusetts, and Connecticut for the first 15 months of the COVID-19 pandemic, from March 1 2020 to May 31 2021. This period includes the initial spring 2020 wave, the major winter wave of 2020-2021, and the lagging wave of lineage B.1.1.7(Alpha) infections during March-April 2021. In autumn 2020, SARS-CoV-2 population immunity (equal to the attack rate at that point) in southern New England was still below 15%, setting the stage for a large winter wave. After the roll-out of vaccines in early 2021, population immunity in many states was expected to approach 70% by spring 2021, with more than half of this immune population coming from vaccinations. Our population immunity estimates for May 31 2021 are 73.4% (95% CrI: 72.9% - 74.1%) for Rhode Island, 64.1% (95% CrI: 64.0% - 64.4%) for Connecticut, and 66.3% (95% CrI: 65.9% - 66.9%) for Massachusetts, indicating that >33% of southern Englanders were still susceptible to infection when the Delta variant began spreading in July 2021. Despite high vaccine coverage in these states, population immunity in summer 2021 was lower than planned due to 34% (Rhode Island), 25% (Connecticut), and 28% (Massachusetts) of vaccine distribution going to seropositive individuals. Future emergency-setting vaccination planning will likely have to consider over-vaccination as a strategy to ensure that high levels of population immunity are reached during the course of an ongoing epidemic.

SARS-CoV-2 epidemic after social and economic reopening in three US states reveals shifts in age structure and clinical characteristics.

In the United States, state-level re-openings in spring 2020 presented an opportunity for the resurgence of SARS-CoV-2 transmission. One important question during this time was whether human contact and mixing patterns could increase gradually without increasing viral transmission, the rationale being that new mixing patterns would likely be associated with improved distancing, masking, and hygiene practices. A second key question to follow during this time was whether clinical characteristics of the epidemic would improve after the initial surge of cases. Here, we analyze age-structured case, hospitalization, and death time series from three states - Rhode Island, Massachusetts, and Pennsylvania - that had successful re-openings in May 2020 without summer waves of infection. Using a Bayesian inference framework on eleven daily data streams and flexible daily population contact parameters, we show that population-average mixing rates dropped by >50% during the lockdown period in March/April, and that the correlation between overall population mobility and transmission-capable mobility was broken in May as these states partially re-opened. We estimate the reporting rates (fraction of symptomatic cases reporting to health system) at 96.0% (RI), 72.1% (MA), and 75.5% (PA); in Rhode Island, when accounting for cases caught through general-population screening programs, the reporting rate estimate is 94.5%. We show that elderly individuals were less able to reduce contacts during the lockdown period when compared to younger individuals. Attack rate estimates through August 31 2020 are 6.4% (95% CI: 5.8% ‒ 7.3%) of the total population infected for Rhode Island, 5.7% (95% CI: 5.0% ‒ 6.8%) in Massachusetts, and 3.7% (95% CI: 3.1% ‒ 4.5%) in Pennsylvania, with some validation available through published seroprevalence studies. Infection fatality rates (IFR) estimates for the spring epidemic are higher in our analysis (>2%) than previously reported values, likely resulting from the epidemics in these three states affecting the most vulnerable sub-populations, especially the most vulnerable of the ≥80 age group.