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1.
Isr J Health Policy Res ; 11(1): 36, 2022 10 20.
Article in English | MEDLINE | ID: covidwho-2079545

ABSTRACT

Mathematical and statistical models have played an important role in the analysis of data from COVID-19. They are important for tracking the progress of the pandemic, for understanding its spread in the population, and perhaps most significantly for forecasting the future course of the pandemic and evaluating potential policy options. This article describes the types of models that were used by research teams in Israel, presents their assumptions and basic elements, and illustrates how they were used, and how they influenced decisions. The article grew out of a "modelists' dialog" organized by the Israel National Institute for Health Policy Research with participation from some of the leaders in the local modeling effort.


Subject(s)
COVID-19 , Humans , Pandemics/prevention & control , SARS-CoV-2 , Israel/epidemiology , Models, Statistical
3.
Isr J Health Policy Res ; 11(1): 22, 2022 04 20.
Article in English | MEDLINE | ID: covidwho-1808383

ABSTRACT

The COVID-19 pandemic cast a dramatic spotlight on the use of data as a fundamental component of good decision-making. Evaluating and comparing alternative policies required information on concurrent infection rates and insightful analysis to project them into the future. Statisticians in Israel were involved in these processes early in the pandemic in some silos as an ad-hoc unorganized effort. Informal discussions within the statistical community culminated in a roundtable, organized by three past presidents of the Israel Statistical Association, and hosted by the Samuel Neaman Institute in April 2021. The meeting was designed to provide a forum for exchange of views on the profession's role during the COVID-19 pandemic, and more generally, on its influence in promoting evidence-based public policy. This paper builds on the insights and discussions that emerged during the roundtable meeting and presents a general framework, with recommendations, for involving statisticians and statistics in decision-making.


Subject(s)
COVID-19 , Humans , Israel/epidemiology , Pandemics/prevention & control , Public Policy
4.
Int J Epidemiol ; 51(3): 727-736, 2022 06 13.
Article in English | MEDLINE | ID: covidwho-1769288

ABSTRACT

BACKGROUND: We aimed to build a basic daily mortality curve in Israel based on 20-year data accounting for long-term and annual trends, influenza-like illness (ILI) and climate factors among others, and to use the basic curve to estimate excess mortality during 65 weeks of the COVID-19 pandemic in 2020-2021 stratified by age groups. METHODS: Using daily mortality counts for the period 1 January 2000 to 31 December 2019, weekly ILI counts, daily climate and yearly population sizes, we fitted a quasi-Poisson model that included other temporal covariates (a smooth yearly trend, season, day of week) to define a basic mortality curve. Excess mortality was calculated as the difference between the observed and expected deaths on a weekly and periodic level. Analyses were stratified by age group. RESULTS: Between 23 March 2020 and 28 March 2021, a total of 51 361 deaths were reported in Israel, which was 12% higher than the expected number for the same period (expected 45 756 deaths; 95% prediction interval, 45 325-46 188; excess deaths, 5605). In the same period, the number of COVID-19 deaths was 6135 (12% of all observed deaths), 9.5% larger than the estimated excess mortality. Stratification by age group yielded a heterogeneous age-dependent pattern. Whereas in ages 90+ years (11% excess), 100% of excess mortality was attributed to COVID-19, in ages 70-79 years there was a greater excess (21%) with only 82% attributed to COVID-19. In ages 60-69 and 20-59 years, excess mortality was 14% and 10%, respectively, and the number of COVID-19 deaths was higher than the excess mortality. In ages 0-19 years, we found 19% fewer deaths than expected. CONCLUSION: The findings of an age-dependent pattern of excess mortality may be related to indirect pathways in mortality risk, specifically in ages <80 years, and to the implementation of the lockdown policies, specifically in ages 0-19 years with lower deaths than expected.


Subject(s)
COVID-19 , Adolescent , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , Communicable Disease Control , Humans , Infant , Infant, Newborn , Israel/epidemiology , Mortality , Pandemics , Seasons , Young Adult
5.
Clin Microbiol Infect ; 28(6): 859-864, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1693758

ABSTRACT

OBJECTIVES: Despite the success in developing COVID-19 vaccines, containment of the disease is obstructed worldwide by vaccine production bottlenecks, logistics hurdles, vaccine refusal, transmission through unvaccinated children, and the appearance of new viral variants. This underscores the need for effective strategies for identifying carriers/patients, which was the main aim of this study. METHODS: We present a bubble-based PCR testing approach using swab-pooling into lysis buffer. A bubble is a cluster of people who can be periodically tested for SARS-CoV-2 by swab-pooling. A positive test of a pool mandates quarantining each of its members, who are then individually tested while in isolation to identify the carrier(s) for further epidemiological contact tracing. RESULTS: We tested an overall sample of 25 831 individuals, divided into 1273 bubbles, with an average size of 20.3 ± 7.7 swabs/test tube, obtaining for all pools (≤37 swabs/pool) a specificity of 97.5% (lower bound 96.6%) and a sensitivity of 86.3% (lower bound 78.2%) and a post hoc analyzed sensitivity of 94.6% (lower bound 86.7%) and a specificity of 97.2% (lower bound 96.2%) in pools with ≤25 swabs, relative to individual testing. DISCUSSION: This approach offers a significant scale-up in sampling and testing throughput and savings in testing cost, without reducing sensitivity or affecting the standard PCR testing laboratory routine. It can be used in school classes, airplanes, hospitals, military units, and workplaces, and may be applicable to future pandemics.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/diagnosis , COVID-19 Testing , COVID-19 Vaccines , Child , Humans , Pandemics , RNA, Viral , SARS-CoV-2/genetics , Sensitivity and Specificity , Specimen Handling
6.
JAMA Pediatr ; 176(5): 470-477, 2022 05 01.
Article in English | MEDLINE | ID: covidwho-1680221

ABSTRACT

Importance: Pregnant women were excluded from the BNT162b2 messenger RNA (mRNA) COVID-19 vaccine (Pfizer-BioNTech) preauthorization trial. Therefore, observational data on vaccine safety for prenatally exposed newborns are critical to inform recommendations on maternal immunization. Objective: To examine whether BNT162b2 mRNA vaccination during pregnancy is associated with adverse neonatal and early infant outcomes among the newborns. Design, Setting, and Participants: Population-based cohort study comprising all singleton live births in March through September 2021, within a large state-mandated health care organization in Israel, followed up until October 31, 2021. Exposure: Maternal BNT162b2 mRNA vaccination during pregnancy. Main Outcomes and Measures: Risk ratios (RR) of preterm birth, small birth weight for gestational age (SGA), congenital malformations, all-cause hospitalizations, and infant death. Stabilized inverse probability weighting was used to adjust for maternal age, timing of conception, parity, socioeconomic status, population subgroup, and maternal influenza immunization status. Results: The cohort included 24 288 eligible newborns (49% female, 96% born at ≥37 weeks' gestation), of whom 16 697 were exposed (n = 2134 and n = 9364 in the first and second trimesters, respectively) to maternal vaccination in utero. Median (IQR) follow-up after birth was 126 days (76-179) among exposed and 152 days (88-209) among unexposed newborns. No substantial differences were observed in preterm birth rates between exposed and unexposed newborns (RR = 0.95; 95% CI, 0.83-1.10) or SGA (RR = 0.97; 95% CI, 0.87-1.08). No significant differences were observed in the incidence of all-cause neonatal hospitalizations (RR = 0.99; 95% CI, 0.88-1.12), postneonatal hospitalizations after birth (RR = 0.95; 95% CI, 0.84-1.07), congenital anomalies (RR = 0.69; 95% CI, 0.44-1.04), or infant mortality over the study period (RR = 0.84; 95% CI, 0.43-1.72). Conclusions and Relevance: This large population-based study found no evident differences between newborns of women who received BNT162b2 mRNA vaccination during pregnancy, vs those of women who were not vaccinated, and contributes to current evidence in establishing the safety of prenatal vaccine exposure to the newborns. Interpretation of study findings is limited by the observational design.


Subject(s)
BNT162 Vaccine , COVID-19 , Pregnancy Outcome , BNT162 Vaccine/adverse effects , COVID-19/epidemiology , COVID-19/prevention & control , Cohort Studies , Female , Humans , Infant , Infant, Newborn , Live Birth , Male , Pregnancy , Pregnancy Outcome/epidemiology , Premature Birth/epidemiology
7.
JAMA ; 326(8): 728-735, 2021 08 24.
Article in English | MEDLINE | ID: covidwho-1427006

ABSTRACT

Importance: Data on BNT162b2 messenger RNA (mRNA) vaccine (Pfizer-BioNTech) effectiveness and safety in pregnancy are currently lacking because pregnant women were excluded from the phase 3 trial. Objective: To assess the association between receipt of BNT162b2 mRNA vaccine and risk of SARS-CoV-2 infection among pregnant women. Design, Setting, and Participants: This was a retrospective cohort study within the pregnancy registry of a large state-mandated health care organization in Israel. Pregnant women vaccinated with a first dose from December 19, 2020, through February 28, 2021, were 1:1 matched to unvaccinated women by age, gestational age, residential area, population subgroup, parity, and influenza immunization status. Follow-up ended on April 11, 2021. Exposures: Exposure was defined by receipt of the BNT162b2 mRNA vaccine. To maintain comparability, nonexposed women who were subsequently vaccinated were censored 10 days after their exposure, along with their matched pair. Main Outcomes and Measures: The primary outcome was polymerase chain reaction-validated SARS-CoV-2 infection at 28 days or more after the first vaccine dose. Results: The cohort included 7530 vaccinated and 7530 matched unvaccinated women, 46% and 33% in the second and third trimester, respectively, with a mean age of 31.1 years (SD, 4.9 years). The median follow-up for the primary outcome was 37 days (interquartile range, 21-54 days; range, 0-70). There were 118 SARS-CoV-2 infections in the vaccinated group and 202 in the unvaccinated group. Among infected women, 88 of 105 (83.8%) were symptomatic in the vaccinated group vs 149 of 179 (83.2%) in the unvaccinated group (P ≥ .99). During 28 to 70 days of follow-up, there were 10 infections in the vaccinated group and 46 in the unvaccinated group. The hazards of infection were 0.33% vs 1.64% in the vaccinated and unvaccinated groups, respectively, representing an absolute difference of 1.31% (95% CI, 0.89%-1.74%), with an adjusted hazard ratio of 0.22 (95% CI, 0.11-0.43). Vaccine-related adverse events were reported by 68 patients; none was severe. The most commonly reported symptoms were headache (n = 10, 0.1%), general weakness (n = 8, 0.1%), nonspecified pain (n = 6, <0.1%), and stomachache (n = 5, <0.1%). Conclusions and Relevance: In this retrospective cohort study of pregnant women, BNT162b2 mRNA vaccination compared with no vaccination was associated with a significantly lower risk of SARS-CoV-2 infection. Interpretation of study findings is limited by the observational design.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/epidemiology , Pregnancy Complications, Infectious/epidemiology , Pregnant Women , Adult , BNT162 Vaccine , COVID-19/immunology , COVID-19/prevention & control , COVID-19 Vaccines/adverse effects , COVID-19 Vaccines/immunology , Case-Control Studies , Confidence Intervals , Female , Gestational Age , Humans , Incidence , Israel/epidemiology , Kaplan-Meier Estimate , Pregnancy , Pregnancy Complications, Infectious/immunology , Pregnancy Complications, Infectious/prevention & control , Regression Analysis , Retrospective Studies , Risk , Time Factors , Vaccination/statistics & numerical data
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