Utilizing direct and indirect information to improve the COVID-19 vaccination booster scheduling.

Current global COVID-19 booster scheduling strategies mainly focus on vaccinating high-risk populations at predetermined intervals. However, these strategies overlook key data: the direct insights into individual immunity levels from active serological testing and the indirect information available either through sample-based sero-surveillance, or vital demographic, location, and epidemiological factors. Our research, employing an age-, risk-, and region-structured mathematical model of disease transmission-based on COVID-19 incidence and vaccination data from Israel between 15 May 2020 and 25 October 2021-reveals that a more comprehensive strategy integrating these elements can significantly reduce COVID-19 hospitalizations without increasing existing booster coverage. Notably, the effective use of indirect information alone can considerably decrease COVID-19 cases and hospitalizations, without the need for additional vaccine doses. This approach may also be applicable in optimizing vaccination strategies for other infectious diseases, including influenza.

Safety of monovalent and bivalent BNT162b2 mRNA COVID-19 vaccine boosters in at-risk populations in Israel: a large-scale, retrospective, self-controlled case series study.

BACKGROUND: COVID-19 continues to be a major health threat, particularly among at-risk groups, including individuals aged 60 years or older and people with particular medical conditions. Nevertheless, the absence of sufficient vaccine safety information is one of the key contributors to vaccine refusal. We aimed to assess the short-term safety profile of the BNT162b2 mRNA COVID-19 vaccine booster doses. METHODS: In this self-controlled case series study, we used a database of members of the largest health-care organisation in Israel. We analysed the medical records of individuals at risk of COVID-19 complications who had received two doses of the monovalent BNT162b2 mRNA COVID-19 vaccine (tozinameran, Pfizer-BioNTech) as their primary course of vaccination and then also received BNT162b2 mRNA COVID-19 vaccine boosters between July 30, 2021, and Nov 28, 2022, as a monovalent first or second booster, or as a bivalent first, second, or third booster, or a combination of these. We included individuals who had active membership of the health-care organisation and who were alive (excluding COVID-19 deaths) throughout the entire study period. We excluded individuals who, during the study period, were either not active Clalit Health Services members or died of non-COVID-19 causes, and those who were infected with COVID-19 during the 7-day period after vaccination. Individuals' at-risk status was assessed on the day before the baseline period started. The primary outcome was non-COVID-19 hospitalisation for 29 adverse events that might be associated with vaccination. For each adverse event, we compared the risk difference of hospitalisation during a 28-day pre-vaccination baseline period versus during a 28-day post-vaccination period, using a non-parametric percentile bootstrap method. FINDINGS: Of the 3 574 243 members of the health-care organisation, 1 073 110 received a first monovalent booster, 394 251 received a second monovalent booster, and 123 084 received a bivalent first, second, or third booster. Overall, we found no indication of an elevated risk of non-COVID-19 hospitalisation following administration of any of the booster vaccines (risk difference in events per 100 000 individuals: first monovalent booster -37·1 [95% CI -49·8 to -24·2]; second monovalent booster -37·8 [-62·2 to -13·2]; and bivalent booster -18·7 [-53·6 to 15·4]). Except for extremely rare elevated risks after the first monovalent booster-of myocarditis (risk difference 0·7 events per 100 000 individuals [95% CI 0·3-1·3]), seizures (2·2 [0·4-4·1]), and thrombocytopenia (2·6 [0·7-4·7])-we found no safety signals in other adverse events, including ischaemic stroke. INTERPRETATION: This study provides the necessary vaccine safety assurances for at-risk populations to receive timed roll-out booster vaccinations. These assurances could reduce vaccine hesitancy and increase the number of at-risk individuals who opt to become vaccinated, and thereby prevent the severe outcomes associated with COVID-19. FUNDING: Israel Science Foundation and Israel Precision Medicine Partnership programme.

Real-time sensing of war's effects on wellbeing with smartphones and smartwatches.

BACKGROUND: Modern wars have a catastrophic effect on the wellbeing of civilians. However, the nature of this effect remains unclear, with most insights gleaned from subjective, retrospective studies. METHODS: We prospectively monitored 954 Israelis (>40 years) from two weeks before the May 2021 Israel-Gaza war until four weeks after the ceasefire using smartwatches and a dedicated mobile application with daily questionnaires on wellbeing. This war severely affected civilians on both sides, where over 4300 rockets and missiles were launched towards Israeli cities, and 1500 aerial, land, and sea strikes were launched towards 16,500 targets in the Gaza Strip. RESULTS: We identify considerable changes in all the examined wellbeing indicators during missile attacks and throughout the war, including spikes in heart rate levels, excessive screen-on time, and a reduction in sleep duration and quality. These changes, however, fade shortly after the war, with all affected measures returning to baseline in nearly all the participants. Greater changes are observed in individuals living closer to the battlefield, women, and younger individuals. CONCLUSIONS: The demonstrated ability to monitor objective and subjective wellbeing indicators during crises in real-time is pivotal for the early detection of and prompt assistance to populations in need.

This study investigated the impact of the May 2021 Israel-Gaza war on the wellbeing of Israeli civilians. To do so, 954 Israelis over the age of 40 were monitored for six weeks before and after the war using smartwatches and a mobile application that asked daily wellbeing questions. The researchers found that during the war, people experienced spikes in heart rate, decreased sleep quality and duration, and increased screen time. These changes were more significant in people living closer to the battlefield, women, and younger individuals. However, after the ceasefire, wellbeing indicators returned to baseline levels. The study shows that monitoring wellbeing in real-time during crises can help identify and assist populations in need.

Risk Factors Associated With de Quervain Tenosynovitis in Postpartum Women.

BACKGROUND: De Quervain (DQ) disease is caused by stenosis of the first dorsal compartment containing the abductor pollicis longus and extensor pollicis brevis. This condition affects women 6 times more than men and is also commonly reported in pregnant and lactating women. The natural course of the disease and associated risk factors are not well understood. In this study, we described the gestational risk factors associated with postpartum DQ. METHODS: Sixty-three postpartum women with DQ were included in final study population. Medical records were reviewed for patient characteristics, including age, comorbidities, and body mass index (BMI), and gestational information, including length of pregnancy, gestation number, single or twin birth, and weight at birth. Odds ratio (OR) for developing DQ tenosynovitis were calculated with the control group of 630 postpartum women without DQ who gave birth between 2012 and 2020 in the same district. RESULTS: Length of pregnancy (>40 weeks, OR = 5.81 [3.29-10.28]), first childbirth (OR = 2.23 [1.32-3.77]), and weight (BMI > 25, OR = 2.08 [1.14-3.81]) were all statistically significant risk factors associated with developing DQ. Number of fetuses > 1 (OR = 0.98 [0.29-3.33]) and birth weight more than 3.5 kg (OR = 0.60 [0.30-1.21]) were not associated with higher risk of DQ. CONCLUSIONS: Gestational risk factors associated with developing postpartum DQ include first pregnancy and long pregnancy of more than 40 weeks. Interestingly, child's birthweight and number of fetuses, both factors that might increase load on the first dorsal compartment while holding the child, were not shown to increase the risk of postpartum DQ.

Safety of the fourth COVID-19 BNT162b2 mRNA (second booster) vaccine: a prospective and retrospective cohort study.

BACKGROUND: The effectiveness of the second BNT162b2 (Pfizer-BioNTech) mRNA COVID-19 booster vaccine dose (ie, fourth inoculation) is well established, but its safety has yet to be fully understood. The absence of sufficient vaccine safety information is one of the key contributors to vaccine hesitancy. In this study, we aimed to evaluate the safety profile of the second BNT162b2 mRNA COVID-19 booster vaccine using data from a retrospective cohort and a prospective cohort. METHODS: To evaluate the safety profile of the second booster vaccine, we analysed its short-term effects and compared them to those of the first booster by using data from, first, a retrospective cohort of 250 000 random members of the second-largest health-care organisation in Israel (Maccabi Healthcare Services) and, second, a prospective cohort (the PerMed study) of 4698 participants from all across Israel. Individuals who were aged 18 years or older who received the second BNT162b2 mRNA COVID-19 vaccine booster during the vaccination campaign, from Dec 30, 2021, to July 22, 2022, were eligible for inclusion in the retrospective cohort analysis. To be included in the PerMed study, participants needed to be 18 years or older, members of Maccabi Healthcare Services at the time of enrolment, using their own smartphone, and be able to give informed consent by themselves. Participants from the prospective cohort received smartwatches, downloaded a dedicated mobile application, and granted access to their medical records. The smartwatches continuously monitored several physiological measures, including heart rate. For analysis of the prospective cohort data, we used the Kruskal-Wallis test to compare heart rate levels observed before and after vaccination. The mobile application collected daily self-reported questionnaires on local and systemic reactions. Medical records of the retrospective cohort were accessed to examine the occurrence of 25 potential adverse events, and we evaluated the risk differences between 42 days in the periods before and after vaccination in a pairwise method using non-parametric percentile bootstrap. FINDINGS: The retrospective cohort included 94 169 participants who received the first booster and 17 814 who received the second booster. Comparing the 42 days before and after vaccination, the second booster was not associated with any of the 25 adverse events investigated, including myocardial infarction (risk difference, 2·25 events per 10 000 individuals [95% CI -3·93 to 8·98]) and Bell's Palsy (-1·68 events [-5·61 to 2·25]). None of the individuals was diagnosed with myocarditis or pericarditis following vaccination with the second booster. The prospective cohort included 1785 participants who received the first booster and 699 who received the second booster. We found no significant differences after inoculation with the first booster compared with the second booster (heart rate: day 2 [p=0·3], day 6 [p=0·89]; extent of self-reported reactions [p=0·06]). We found a significant increase in mean heart rate relative to that observed during the week before vaccination (baseline) levels during the first 3 days following the second booster (p<0·0001), peaking on day 2 (mean difference of 1·61 bpm [1·07 to 2·16] compared with baseline). Mean heart rate values returned to baseline levels by day 6 (-0·055 bpm [-0·56 to 0·45] compared with baseline). INTERPRETATION: Both our retrospective and prospective analyses support the safety of the second booster, with our findings reflecting physicians' diagnoses, patients' objective physiological measures, and patients' subjective reactions. We believe this study provides safety assurances to the global population who are eligible to receive an additional COVID-19 booster inoculation. These assurances can help increase the number of high-risk individuals who opt to receive this booster vaccine and thereby prevent severe outcomes associated with COVID-19. FUNDING: European Research Council (ERC).

Self-Reported and Physiologic Reactions to Third BNT162b2 mRNA COVID-19 (Booster) Vaccine Dose.

Despite extensive technological advances in recent years, objective and continuous assessment of physiologic measures after vaccination is rarely performed. We conducted a prospective observational study to evaluate short-term self-reported and physiologic reactions to the booster BNT162b2 mRNA (Pfizer-BioNTech, https://www.pfizer.com) vaccine dose. A total of 1,609 participants were equipped with smartwatches and completed daily questionnaires through a dedicated mobile application. The extent of systemic reactions reported after the booster dose was similar to that of the second dose and considerably greater than that of the first dose. Analyses of objective heart rate and heart rate variability measures recorded by smartwatches further supported this finding. Subjective and objective reactions after the booster dose were more apparent in younger participants and in participants who did not have underlying medical conditions. Our findings further support the safety of the booster dose from subjective and objective perspectives and underscore the need for integrating wearables in clinical trials.

Utilizing wearable sensors for continuous and highly-sensitive monitoring of reactions to the BNT162b2 mRNA COVID-19 vaccine.

Background: Clinical trial guidelines for assessing the safety of vaccines, are primarily based on self-reported questionnaires. Despite the tremendous technological advances in recent years, objective, continuous assessment of physiological measures post-vaccination is rarely performed. Methods: We conducted a prospective observational study during the mass vaccination campaign in Israel. 160 participants >18 years who were not previously found to be COVID-19 positive and who received the BNT162b2 COVID-19 (Pfizer BioNTech) vaccine were equipped with an FDA-approved chest-patch sensor and a dedicated mobile application. The chest-patch sensor continuously monitored 13 different cardiovascular, and hemodynamic vitals: heart rate, blood oxygen saturation, respiratory rate, systolic and diastolic blood pressure, pulse pressure, mean arterial pressure, heart rate variability, stroke volume, cardiac output, cardiac index, systemic vascular resistance and skin temperature. The mobile application collected daily self-reported questionnaires on local and systemic reactions. Results: We identify continuous and significant changes following vaccine administration in nearly all vitals. Markedly, these changes are observed even in presumably asymptomatic participants who did not report any local or systemic reaction. Changes in vitals are more apparent at night, in younger participants, and in participants following the second vaccine dose. Conclusion: the considerably higher sensitivity of wearable sensors can revolutionize clinical trials by enabling earlier identification of abnormal reactions with fewer subjects.

A multi-layer model for the early detection of COVID-19.

Current COVID-19 screening efforts mainly rely on reported symptoms and the potential exposure to infected individuals. Here, we developed a machine-learning model for COVID-19 detection that uses four layers of information: (i) sociodemographic characteristics of the individual, (ii) spatio-temporal patterns of the disease, (iii) medical condition and general health consumption of the individual and (iv) information reported by the individual during the testing episode. We evaluated our model on 140 682 members of Maccabi Health Services who were tested for COVID-19 at least once between February and October 2020. These individuals underwent, in total, 264 516 COVID-19 PCR tests, out of which 16 512 were positive. Our multi-layer model obtained an area under the curve (AUC) of 81.6% when evaluated over all the individuals in the dataset, and an AUC of 72.8% when only individuals who did not report any symptom were included. Furthermore, considering only information collected before the testing episode-i.e. before the individual had the chance to report on any symptom-our model could reach a considerably high AUC of 79.5%. Our ability to predict early on the outcomes of COVID-19 tests is pivotal for breaking transmission chains, and can be used for a more efficient testing policy.

Early detection of COVID-19 outbreaks using human mobility data.

BACKGROUND: Contact mixing plays a key role in the spread of COVID-19. Thus, mobility restrictions of varying degrees up to and including nationwide lockdowns have been implemented in over 200 countries. To appropriately target the timing, location, and severity of measures intended to encourage social distancing at a country level, it is essential to predict when and where outbreaks will occur, and how widespread they will be. METHODS: We analyze aggregated, anonymized health data and cell phone mobility data from Israel. We develop predictive models for daily new cases and the test positivity rate over the next 7 days for different geographic regions in Israel. We evaluate model goodness of fit using root mean squared error (RMSE). We use these predictions in a five-tier categorization scheme to predict the severity of COVID-19 in each region over the next week. We measure magnitude accuracy (MA), the extent to which the correct severity tier is predicted. RESULTS: Models using mobility data outperformed models that did not use mobility data, reducing RMSE by 17.3% when predicting new cases and by 10.2% when predicting the test positivity rate. The best set of predictors for new cases consisted of 1-day lag of past 7-day average new cases, along with a measure of internal movement within a region. The best set of predictors for the test positivity rate consisted of 3-days lag of past 7-day average test positivity rate, along with the same measure of internal movement. Using these predictors, RMSE was 4.812 cases per 100,000 people when predicting new cases and 0.79% when predicting the test positivity rate. MA in predicting new cases was 0.775, and accuracy of prediction to within one tier was 1.0. MA in predicting the test positivity rate was 0.820, and accuracy to within one tier was 0.998. CONCLUSIONS: Using anonymized, macro-level data human mobility data along with health data aids predictions of when and where COVID-19 outbreaks are likely to occur. Our method provides a useful tool for government decision makers, particularly in the post-vaccination era, when focused interventions are needed to contain COVID-19 outbreaks while mitigating the collateral damage from more global restrictions.

BNT162b2 vaccination effectively prevents the rapid rise of SARS-CoV-2 variant B.1.1.7 in high-risk populations in Israel.

Since the emergence of the SARS-CoV-2 pandemic, various genetic variants have been described. The B.1.1.7 variant, which emerged in England during December 2020, is associated with increased infectivity. Therefore, its pattern of spread is of great importance. The Israeli government established three national programs: massive RT-PCR testing, focused surveillance in nursing homes, and robust prioritized vaccination with BNT162b2. To define the impact of the aforementioned programs, we analyze data from ∼300,000 RT-PCR samples collected from December 6, 2020, to February 10, 2021. We reveal that the B.1.1.7 is 45% (95% confidence interval [CI]: 20%-60%) more transmissible than the wild-type strain and has become the dominant strain in Israel within 3.5 weeks. Despite the rapid increase in viral spread, focused RT-PCR testing and prioritized vaccination programs are capable of preventing the spread of the B.1.1.7 variant in the elderly. Therefore, proactive surveillance programs, combined with prioritized vaccination, are achievable and can reduce severe illness and subsequent death.

Human mobility and poverty as key drivers of COVID-19 transmission and control.

BACKGROUND: Applying heavy nationwide restrictions is a powerful method to curtail COVID-19 transmission but poses a significant humanitarian and economic crisis. Thus, it is essential to improve our understanding of COVID-19 transmission, and develop more focused and effective strategies. As human mobility drives transmission, data from cellphone devices can be utilized to achieve these goals. METHODS: We analyzed aggregated and anonymized mobility data from the cell phone devices of> 3 million users between February 1, 2020, to May 16, 2020 - in which several movement restrictions were applied and lifted in Israel. We integrated these mobility patterns into age-, risk- and region-structured transmission model. Calibrated to coronavirus incidence in 250 regions covering Israel, we evaluated the efficacy and effectiveness in decreasing morbidity and mortality of applying localized and temporal lockdowns (stay-at-home order). RESULTS: Poorer regions exhibited lower and slower compliance with the restrictions. Our transmission model further indicated that individuals from impoverished areas were associated with high transmission rates. Considering a horizon of 1-3 years, we found that to reduce COVID-19 mortality, school closure has an adverse effect, while interventions focusing on the elderly are the most efficient. We also found that applying localized and temporal lockdowns during regional outbreaks reduces the overall mortality and morbidity compared to nationwide lockdowns. These trends were consistent across vast ranges of epidemiological parameters, and potential seasonal forcing. CONCLUSIONS: More resources should be devoted to helping impoverished regions. Utilizing cellphone data despite being anonymized and aggregated can help policymakers worldwide identify hotspots and apply designated strategies against future COVID-19 outbreaks.

Optimizing antiviral treatment for seasonal influenza in the USA: a mathematical modeling analysis.

BACKGROUND: Seasonal influenza remains a major cause of morbidity and mortality in the USA. Despite the US Centers for Disease Control and Prevention recommendation promoting the early antiviral treatment of high-risk patients, treatment coverage remains low. METHODS: To evaluate the population-level impact of increasing antiviral treatment timeliness and coverage among high-risk patients in the USA, we developed an influenza transmission model that incorporates data on infectious viral load, social contact, and healthcare-seeking behavior. We modeled the reduction in transmissibility in treated individuals based on their reduced daily viral load. The reduction in hospitalizations following treatment was based on estimates from clinical trials. We calibrated the model to weekly influenza data from Texas, California, Connecticut, and Virginia between 2014 and 2019. We considered in the baseline scenario that 2.7-4.8% are treated within 48 h of symptom onset while an additional 7.3-12.8% are treated after 48 h of symptom onset. We evaluated the impact of improving the timeliness and uptake of antiviral treatment on influenza cases and hospitalizations. RESULTS: Model projections suggest that treating high-risk individuals as early as 48 h after symptom onset while maintaining the current treatment coverage level would avert 2.9-4.5% of all symptomatic cases and 5.5-7.1% of all hospitalizations. Geographic variability in the effectiveness of earlier treatment arises primarily from variabilities in vaccination coverage and population demographics. Regardless of these variabilities, we found that when 20% of the high-risk individuals were treated within 48 h, the reduction in hospitalizations doubled. We found that treatment of the elderly population (> 65 years old) had the highest impact on reducing hospitalizations, whereas treating high-risk individuals aged 5-19 years old had the highest impact on reducing transmission. Furthermore, the population-level benefit per treated individual is enhanced under conditions of high vaccination coverage and a low attack rate during an influenza season. CONCLUSIONS: Increased timeliness and coverage of antiviral treatment among high-risk patients have the potential to substantially reduce the burden of seasonal influenza in the USA, regardless of influenza vaccination coverage and the severity of the influenza season.

Tdap vaccination during pregnancy interrupts a twenty-year increase in the incidence of pertussis.

Pertussis incidence in developed countries, including Israel, has increased over the past two decades despite the addition of two booster doses in children. However, as pertussis is characterized by a multi-annual periodicity, and since clinical diagnosis can miss cases, determining disease trends at the population level is challenging. To bridge this gap, we developed a simple statistical model to capture the temporal patterns of pertussis incidence in Israel. Our model was calibrated and tested using laboratory-confirmed cases of pertussis for the Israeli population between 1998 and 2019. The model identifies a clear four-year periodicity of pertussis incidence over the past two decades that is identical to the one observed in the pre-vaccine era. Accounting for this periodicity, the model shows a 325% increase in pertussis incidence from 2002 to 2014. These multi-year trends were interrupted shortly after the introduction of routine immunization of Tdap vaccine in pregnancy in 2015, after which we found a 59.7% (95% CI: 57.7-61.6%)decline in pertussis incidence and a 49.5% (36.0-61.6%) decline in hospitalizations compared to the model's projection. While this sharp decline cannot be fully attributed to the newly introduced vaccination policy, sharper reductions of 71.2% (65.6-76.1%) in incidence and 58.4% (39.6-72.7%) in hospitalizations, have been observed in infants of age two months and below - young infants that have yet to become vaccinated and are more likely to be protected by maternal vaccination. Our work suggests that Tdap vaccination during pregnancy is a promising policy for controlling pertussis. Furthermore, due to the stable periodicity of pertussis, public health decision-makers should invest continuous efforts in the implementation of this strategy with additional reinforcement in expected peak years.