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1.
Clin Infect Dis ; 2022 May 25.
Article in English | MEDLINE | ID: covidwho-1927312

ABSTRACT

BACKGROUND: The Omicron variant of SARS-CoV-2 is highly transmissible in vaccinated and unvaccinated populations. The dynamics governing its establishment and propensity towards fixation (reaching 100% frequency in the SARS-CoV-2 population) in communities remain unknown. In this work, we describe the dynamics of Omicron at three institutions of higher education (IHEs) in the greater Boston area. METHODS: We use diagnostic and variant-specifying molecular assays and epidemiological analytical approaches to describe the rapid dominance of Omicron following its introduction to three IHEs with asymptomatic surveillance programs. RESULTS: We show that the establishment of Omicron at IHEs precedes that of the state and region, and that the time to fixation is shorter at IHEs (9.5-12.5 days) than in the state (14.8 days) or region. We show that the trajectory of Omicron fixation among university employees resembles that of students, with a 2-3 day delay. Finally, we compare cycle threshold (Ct) values in Omicron vs. Delta variant cases on college campuses, and identify lower viral loads among college affiliates harboring Omicron infections. CONCLUSIONS: We document the rapid takeover of the Omicron variant at IHEs, reaching near-fixation within the span of 9.5-12.5 days despite lower viral loads, on average, than the previously dominant Delta variant. These findings highlight the transmissibility of Omicron, its propensity to rapidly dominate small populations, and the ability of robust asymptomatic surveillance programs to offer early insights into the dynamics of pathogen arrival and spread.

2.
JAMA Netw Open ; 5(5): e2214171, 2022 05 02.
Article in English | MEDLINE | ID: covidwho-1864298

ABSTRACT

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.


Subject(s)
COVID-19 , SARS-CoV-2 , Adult , Bayes Theorem , COVID-19/epidemiology , COVID-19 Vaccines/therapeutic use , Humans , Incidence , New England
4.
Commun Biol ; 5(1): 439, 2022 05 11.
Article in English | MEDLINE | ID: covidwho-1839575

ABSTRACT

SARS-CoV-2 variants shaped the second year of the COVID-19 pandemic and the discourse around effective control measures. Evaluating the threat posed by a new variant is essential for adapting response efforts when community transmission is detected. In this study, we compare the dynamics of two variants, Alpha and Iota, by integrating genomic surveillance data to estimate the effective reproduction number (Rt) of the variants. We use Connecticut, United States, in which Alpha and Iota co-circulated in 2021. We find that the Rt of these variants were up to 50% larger than that of other variants. We then use phylogeography to show that while both variants were introduced into Connecticut at comparable frequencies, clades that resulted from introductions of Alpha were larger than those resulting from Iota introductions. By monitoring the dynamics of individual variants throughout our study period, we demonstrate the importance of routine surveillance in the response to COVID-19.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Genomics , Humans , Pandemics , SARS-CoV-2/genetics , United States/epidemiology
7.
Water Res ; 212: 118070, 2022 Apr 01.
Article in English | MEDLINE | ID: covidwho-1621092

ABSTRACT

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. 24-hour composite wastewater samples were collected from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and SARS-CoV-2 RNA concentrations were measured using RT-qPCR. The relationship between wastewater copy numbers of SARS-CoV-2 gene fragments and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater copy numbers of SARS-CoV-2 gene fragments and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. The WC ratio increases after key events, providing insight into the balance between disease spread and public health response. Time lag and transfer function analysis showed that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity, which allows for more timely case detection and reporting. These three metrics could help further integrate wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.


Subject(s)
COVID-19 , Pandemics , Benchmarking , Humans , RNA, Viral , SARS-CoV-2 , Waste Water , Wastewater-Based Epidemiological Monitoring
8.
Open forum infectious diseases ; 8(Suppl 1):S290-S290, 2021.
Article in English | EuropePMC | ID: covidwho-1602337

ABSTRACT

Background SARS-CoV-2 continues to spread globally, including in limited resource settings. It is therefore important to derive general case definitions that can be useful and accurate in the absence of timely test results. We aim to validate the World Health Organization (WHO) case definition, a symptom-screening tool currently used to identify SARS-CoV-2 cases in a cohort of symptomatic health care providers (HCP) who completed a symptom survey interview and received a PCR test at Boston Medical Center (BMC) between March 13, 2020 and May 5, 2020. Methods We classified each HCP as a probable or not probable case of SARS-CoV-2 based on the WHO case definition. Using PCR test as gold standard, we computed the sensitivity and specificity of the WHO case definition. We used a stepwise logistic regression model on all PCR-tested HCP to identify symptoms predictive of PCR positivity. Results Of 328 included HCP, 109 (33.2%) were PCR positive, 213 (64.9%) negative, and 6 (1.8%) had indeterminate test result. The sensitivity and specificity of the WHO case definition were 65.1% and 74.6%, respectively. The positive predictive value was 56.8% and the negative predictive value was 80.7%. Symptoms found to be predictive of PCR positivity were fever, headache, loss of smell and/or loss of taste, and muscle ache/joint pain. Sore throat was found to be predictive of PCR negativity. The area under the curve using the final model was 0.8412. All statistically significant symptoms included in the final model, were also included in the WHO case definition. Conclusion In our largely symptomatic HCP cohort, our model yielded similar symptoms to those identified in the WHO probable case definition. As seen in similar studies, it is unlikely that further adjustment will improve the performance of a SARS-CoV-2 case definition. However, it is concerning that 35% (38/109) of PCR positive SARS-CoV-2 HCP would have been classified as not probable cases by the WHO definition, given that this definition does not even include asymptomatic cases. This is further evidence for global building of laboratory capacity and development of affordable diagnostics to improve global pandemic control. Disclosures All Authors: No reported disclosures

9.
Open Forum Infect Dis ; 8(10): ofab465, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1526182

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19) vaccine trials and post-implementation data suggest that vaccination decreases infections. We examine vaccination's impact on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) case rates and viral diversity among health care workers (HCWs) during a high community prevalence period. METHODS: In this prospective cohort study, HCW received 2 doses of BNT162b2 or mRNA-1273. We included confirmed cases among HCWs from 9 December 2020 to 23 February 2021. Weekly SARS-CoV-2 rates per 100,000 person-days and by time from first injection (1-14 and ≥15 days) were compared with surrounding community rates. Viral genomes were sequenced. RESULTS: SARS-CoV-2 cases occurred in 1.4% (96/7109) of HCWs given at least a first dose and 0.3% (17/5913) of HCWs given both vaccine doses. Adjusted rate ratios (95% confidence intervals) were 0.73 (.53-1.00) 1-14 days and 0.18 (.10-.32) ≥15 days from first dose. HCW ≥15 days from initial dose compared to 1-14 days were more often older (46 vs 38 years, P = .007), Latinx (10% vs 8%, P = .03), and asymptomatic (48% vs 11%, P = .0002). SARS-CoV-2 rates among HCWs fell below the surrounding community, an 18% vs 11% weekly decrease, respectively (P = .14). Comparison of 50 genomes from post-first dose cases did not indicate selection pressure toward known spike antibody escape mutations. CONCLUSIONS: Our results indicate an early positive impact of vaccines on SARS-CoV-2 case rates. Post-vaccination isolates did not show unusual genetic diversity or selection for mutations of concern.

10.
Cell ; 184(26): 6229-6242.e18, 2021 12 22.
Article in English | MEDLINE | ID: covidwho-1520753

ABSTRACT

SARS-CoV-2 variants of concern exhibit varying degrees of transmissibility and, in some cases, escape from acquired immunity. Much effort has been devoted to measuring these phenotypes, but understanding their impact on the course of the pandemic-especially that of immune escape-has remained a challenge. Here, we use a mathematical model to simulate the dynamics of wild-type and variant strains of SARS-CoV-2 in the context of vaccine rollout and nonpharmaceutical interventions. We show that variants with enhanced transmissibility frequently increase epidemic severity, whereas those with partial immune escape either fail to spread widely or primarily cause reinfections and breakthrough infections. However, when these phenotypes are combined, a variant can continue spreading even as immunity builds up in the population, limiting the impact of vaccination and exacerbating the epidemic. These findings help explain the trajectories of past and present SARS-CoV-2 variants and may inform variant assessment and response in the future.


Subject(s)
COVID-19/immunology , COVID-19/transmission , Immune Evasion , SARS-CoV-2/immunology , COVID-19/epidemiology , COVID-19/virology , Computer Simulation , Humans , Immunity , Models, Biological , Reinfection , Vaccination
11.
Non-conventional in English | [Unspecified Source], Grey literature | ID: grc-750345

ABSTRACT

Non-pharmaceutical interventions (NPIs) have been crucial in curbing COVID-19 in the United States (US). Consequently, relaxing NPIs through a phased re-opening of the US amid still-high levels of COVID-19 susceptibility could lead to new epidemic waves. This calls for a COVID-19 early warning system. Here we evaluate multiple digital data streams as early warning indicators of increasing or decreasing state-level US COVID-19 activity between January and June 2020. We estimate the timing of sharp changes in each data stream using a simple Bayesian model that calculates in near real-time the probability of exponential growth or decay. Analysis of COVID-19-related activity on social network microblogs, Internet searches, point-of-care medical software, and a metapopulation mechanistic model, as well as fever anomalies captured by smart thermometer networks, shows exponential growth roughly 2-3 weeks prior to comparable growth in confirmed COVID-19 cases and 3-4 weeks prior to comparable growth in COVID-19 deaths across the US over the last 6 months. We further observe exponential decay in confirmed cases and deaths 5-6 weeks after implementation of NPIs, as measured by anonymized and aggregated human mobility data from mobile phones. Finally, we propose a combined indicator for exponential growth in multiple data streams that may aid in developing an early warning system for future COVID-19 outbreaks. These efforts represent an initial exploratory framework, and both continued study of the predictive power of digital indicators as well as further development of the statistical approach are needed.

12.
National Bureau of Economic Research Working Paper Series ; No. 27597, 2020.
Article in English | NBER, Grey literature | ID: grc-748180

ABSTRACT

To assess age-specific infection fatality rates (IFRs) for COVID-19, we have conducted a systematic review of seroprevalence studies as well as countries with comprehensive tracing programs. Age-specific IFRs were computed using the prevalence data in conjunction with reported fatalities four weeks after the midpoint date of each study, reflecting typical lags in fatalities and reporting. Using metaregression procedures, we find a highly significant log-linear relationship between age and IFR for COVID-19. The estimated age-specific IFRs are very low for children and younger adults but increase progressively to 0.4% at age 55, 1.3% at age 65, 4.2% at age 75, and 14% at age 85. About 90% of the geographical variation in population IFR is explained by differences in age composition of the population and age-specific prevalence. These results indicate that COVID-19 is hazardous not only for the elderly but also for middle-aged adults. Moreover, the population IFR for COVID-19 should not be viewed as a fixed parameter but as intrinsically linked to the age-specific pattern of infections. Consequently, public health measures to protect vulnerable age groups could substantially decrease total deaths.

13.
Adv Parasitol ; 114: 1-26, 2021.
Article in English | MEDLINE | ID: covidwho-1458847

ABSTRACT

Human parasitic infections-including malaria, and many neglected tropical diseases (NTDs)-have long represented a Gordian knot in global public health: ancient, persistent, and exceedingly difficult to control. With the coronavirus disease (Covid-19) pandemic substantially interrupting control programmes worldwide, there are now mounting fears that decades of progress in controlling global parasitic infections will be undone. With Covid-19 moreover exposing deep vulnerabilities in the global health system, the current moment presents a watershed opportunity to plan future efforts to reduce the global morbidity and mortality associated with human parasitic infections. In this chapter, we first provide a brief epidemiologic overview of the progress that has been made towards the control of parasitic diseases between 1990 and 2019, contrasting these fragile gains with the anticipated losses as a result of Covid-19. We then argue that the complementary aspirations of the United Nations Sustainable Development Goals (SDGs) and the World Health Organization (WHO)'s 2030 targets for parasitic disease control may be achieved by aligning programme objectives within the One Health paradigm, recognizing the interdependence between humans, animals, and the environment. In so doing, we note that while the WHO remains the preeminent international institution to address some of these transdisciplinary concerns, its underlying challenges with funding, authority, and capacity are likely to reverberate if left unaddressed. To this end, we conclude by reimagining how models of multisectoral global health governance-combining the WHO's normative and technical leadership with greater support in allied policy-making areas-can help sustain future malaria and NTD elimination efforts.


Subject(s)
COVID-19 , One Health , Parasitic Diseases , Tropical Medicine , Animals , Global Health , Humans , Neglected Diseases/epidemiology , Neglected Diseases/prevention & control , Parasitic Diseases/epidemiology , Parasitic Diseases/prevention & control , SARS-CoV-2
15.
Science ; 371(6529)2021 02 05.
Article in English | MEDLINE | ID: covidwho-1388436

ABSTRACT

Analysis of 772 complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from early in the Boston-area epidemic revealed numerous introductions of the virus, a small number of which led to most cases. The data revealed two superspreading events. One, in a skilled nursing facility, led to rapid transmission and significant mortality in this vulnerable population but little broader spread, whereas other introductions into the facility had little effect. The second, at an international business conference, produced sustained community transmission and was exported, resulting in extensive regional, national, and international spread. The two events also differed substantially in the genetic variation they generated, suggesting varying transmission dynamics in superspreading events. Our results show how genomic epidemiology can help to understand the link between individual clusters and wider community spread.


Subject(s)
COVID-19/epidemiology , Genome, Viral , Phylogeny , SARS-CoV-2/genetics , Boston/epidemiology , COVID-19/transmission , Disease Outbreaks , Epidemiological Monitoring , Humans
17.
Sci Total Environ ; 805: 150121, 2022 Jan 20.
Article in English | MEDLINE | ID: covidwho-1386609

ABSTRACT

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we quantify the SARS-CoV-2 concentration and track its dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral load as a convolution of back-dated new clinical cases with the average population-level viral shedding function. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. This finding suggests that SARS-CoV-2 concentrations in wastewater may be primarily driven by viral shedding early in infection. This work shows that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and infer early viral shedding dynamics for newly infected individuals, which are difficult to capture in clinical investigations.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , RNA, Viral , Virus Shedding , Waste Water
18.
Cell Host Microbe ; 29(7): 1048-1051, 2021 07 14.
Article in English | MEDLINE | ID: covidwho-1309196

ABSTRACT

If enough individuals in a population are immune to a pathogen, it cannot cause an outbreak. Deliberately seeking such herd immunity through infection during a potentially lethal pandemic is contrary to all principles of public health, given the potential for uncontrolled outbreaks and risks to vulnerable populations.


Subject(s)
COVID-19/immunology , Immunity, Herd , Pandemics , COVID-19/transmission , COVID-19 Vaccines , Disease Outbreaks , Humans , Public Health , SARS-CoV-2 , Vaccination
19.
BMC Med ; 19(1): 162, 2021 07 13.
Article in English | MEDLINE | ID: covidwho-1308097

ABSTRACT

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.


Subject(s)
COVID-19 Vaccines/supply & distribution , COVID-19 , Communicable Disease Control/organization & administration , Health Care Rationing/organization & administration , Resource Allocation/organization & administration , Vaccination Coverage , Vaccination , Age Factors , COVID-19/epidemiology , COVID-19/prevention & control , Humans , Incidence , Massachusetts/epidemiology , Models, Theoretical , Public Health/methods , Public Health/standards , Rhode Island/epidemiology , SARS-CoV-2 , Vaccination/methods , Vaccination/statistics & numerical data , Vaccination Coverage/statistics & numerical data , Vaccination Coverage/supply & distribution
20.
Water Res ; 202: 117400, 2021 Sep 01.
Article in English | MEDLINE | ID: covidwho-1294290

ABSTRACT

Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.


Subject(s)
COVID-19 , SARS-CoV-2 , Disease Outbreaks , Humans , RNA, Viral , Waste Water
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