Assessing the heterogeneity in the transmission of infectious diseases from time series of epidemiological data.

Structural features and the heterogeneity of disease transmissions play an essential role in the dynamics of epidemic spread. But these aspects can not completely be assessed from aggregate data or macroscopic indicators such as the effective reproduction number. We propose in this paper an index of effective aggregate dispersion (EffDI) that indicates the significance of infection clusters and superspreading events in the progression of outbreaks by carefully measuring the level of relative stochasticity in time series of reported case numbers using a specially crafted statistical model for reproduction. This allows to detect potential transitions from predominantly clustered spreading to a diffusive regime with diminishing significance of singular clusters, which can be a decisive turning point in the progression of outbreaks and relevant in the planning of containment measures. We evaluate EffDI for SARS-CoV-2 case data in different countries and compare the results with a quantifier for the socio-demographic heterogeneity in disease transmissions in a case study to substantiate that EffDI qualifies as a measure for the heterogeneity in transmission dynamics.

Using Shapes of COVID-19 Positive Patient-Specific Trajectories for Mortality Prediction.

Machine learning can be used to identify relevant trajectory shape features for improved predictive risk modeling, which can help inform decisions for individualized patient management in intensive care during COVID-19 outbreaks. We present explainable random forests to dynamically predict next day mortality risk in COVID -19 positive and negative patients admitted to the Mount Sinai Health System between March 1st and June 8th, 2020 using patient time-series data of vitals, blood and other laboratory measurements from the previous 7 days. Three different models were assessed by using time series with: 1) most recent patient measurements, 2) summary statistics of trajectories (min/max/median/first/last/count), and 3) coefficients of fitted cubic splines to trajectories. AUROC and AUPRC with cross-validation were used to compare models. We found that the second and third models performed statistically significantly better than the first model. Model interpretations are provided at patient-specific level to inform resource allocation and patient care.

The indirect impacts of nonpharmacological COVID-19 control measures on other infectious diseases in Yinchuan, Northwest China: a time series study.

BACKGROUND: Various nonpharmaceutical interventions (NPIs) against COVID-19 continue to have an impact on socioeconomic and population behaviour patterns. However, the effect of NPIs on notifiable infectious diseases remains inconclusive due to the variability of the disease spectrum, high-incidence endemic diseases and environmental factors across different geographical regions. Thus, it is of public health interest to explore the influence of NPIs on notifiable infectious diseases in Yinchuan, Northwest China. METHODS: Based on data on notifiable infectious diseases (NIDs), air pollutants, meteorological data, and the number of health institutional personnel in Yinchuan, we first fitted dynamic regression time series models to the incidence of NIDs from 2013 to 2019 and then estimated the incidence for 2020. Then, we compared the projected time series data with the observed incidence of NIDs in 2020. We calculated the relative reduction in NIDs at different emergency response levels in 2020 to identify the impacts of NIPs on NIDs in Yinchuan. RESULTS: A total of 15,711 cases of NIDs were reported in Yinchuan in 2020, which was 42.59% lower than the average annual number of cases from 2013 to 2019. Natural focal diseases and vector-borne infectious diseases showed an increasing trend, as the observed incidence in 2020 was 46.86% higher than the estimated cases. The observed number of cases changed in respiratory infectious diseases, intestinal infectious diseases and sexually transmitted or bloodborne diseases were 65.27%, 58.45% and 35.01% higher than the expected number, respectively. The NIDs with the highest reductions in each subgroup were hand, foot, and mouth disease (5854 cases), infectious diarrhoea (2157 cases) and scarlet fever (832 cases), respectively. In addition, it was also found that the expected relative reduction in NIDs in 2020 showed a decline across different emergency response levels, as the relative reduction dropped from 65.65% (95% CI: -65.86%, 80.84%) during the level 1 response to 52.72% (95% CI: 20.84%, 66.30%) during the level 3 response. CONCLUSIONS: The widespread implementation of NPIs in 2020 may have had significant inhibitory effects on the incidence of respiratory infectious diseases, intestinal infectious diseases and sexually transmitted or bloodborne diseases. The relative reduction in NIDs during different emergency response levels in 2020 showed a declining trend as the response level changed from level 1 to level 3. These results can serve as essential guidance for policy-makers and stakeholders to take specific actions to control infectious diseases and protect vulnerable populations in the future.

Association between matched chronotype and poor mental health among shift workers: a systematic review and meta-analysis.

BACKGROUND: Nearly 0.7 billion workers are involved in the shift work system, leading to concerns about its potential impacts on the large-scale population mental health. This study aimed to synthesise evidence of the associations between matched chronotype and the risk of poor mental health among shift workers. METHODS: Six computerised databases were searched from inception to September 2022. Observational studies were selected if they reported any association between common mental health parameters and chronotype scores/types of shift workers. The Preferred Reporting Items for Systematic Reviews and Meta-analyses checklist was followed. We extracted adjusted risk estimates to calculate pooled effect sizes and explore sources of heterogeneity. The study was registered in PROSPERO: CRD42022357437. RESULTS: Fourteen studies including 49 909 workers were identified. Ever shift workers had a higher risk of poor mental health than the day workers (pooled OR 1.15, 95% CI 1.03 to 1.28; I2=14%, p=0.29), with the evening chronotype ever shift workers having a 1.47 times higher risk than those who worked during the day (pooled OR 1.47, 95% CI 1.13 to 1.91; I2=42%, p=0.16). Sensitivity analysis excluding studies with the highest risk of bias of each group demonstrated consistent findings. CONCLUSIONS: Evening chronotype ever shift workers have poorer mental health than shift workers with other chronotypes. Chronotype remains unrecognised in the contemporary rostering system, making it a hidden contributor to occupational mental health. Work-related physical and mental stresses may be prevented/mitigated with further investigation on optimising shift work schedule combined with individual chronotype preference.

Prevalence and temporal trend of prematurity in Brazil before and during the COVID-19 pandemic: a historical time series analysis, 2011-2021.

OBJECTIVE: to measure the prevalence of prematurity according to the Brazilian macro-regions and maternal characteristics over the past 11 years; to compare the proportions during the COVID-19 pandemic (2020-2021) with those of the historical series (2011-2019). METHODS: this was an ecological study, with data from the Live Birth Information System; the prevalence was calculated according to year, macro-region and maternal characteristics; time series analysis was performed using Prais-Winsten regression model. RESULTS: the prevalence of preterm birth in 2011-2021 was 11.1%, stable; the average in the pandemic period 11.3% (95%CI 11.2;11.4%) was similar to that of the base period 11.0% (95%CI 10.6;11.5%); the North region (11.6%) showed the highest proportion between 2011 and 2021; twin pregnancy (56.3%) and pregnant women who had 4-6 prenatal care visits (16.7%) showed an increasing trend (p-value < 0.001); the highest prevalence was observed for extremes of maternal age, pregnant women of Black race/skin color, indigenous women and those with lower level of education. CONCLUSION: preterm birth rates were highest for socially vulnerable pregnant women, twin pregnancies and in the North; stable prevalence, with no difference between periods.

Impact of the COVID-19 restrictions on the epidemiology of Cryptosporidium spp. in England and Wales, 2015-2021: a time series analysis.

Introduction. In England and Wales, cryptosporidiosis cases peak in spring and autumn, associated with zoonotic/environmental exposures (Cryptosporidium parvum, spring/autumn) and overseas travel/water-based activities (Cryptosporidium hominis, autumn). Coronavirus disease 2019 (COVID-19) restrictions prevented social mixing, overseas travel and access to venues (swimming pools/restaurants) for many months, potentially increasing environmental exposures as people sought alternative countryside activities.Hypothesis. COVID-19 restrictions reduced incidence of C. hominis cases and potentially increased incidence of C. parvum cases.Aim. To inform/strengthen surveillance programmes, we investigated the impact of COVID-19 restrictions on the epidemiology of C. hominis and C. parvum cases.Methodology. Cases were extracted from the Cryptosporidium Reference Unit (CRU) database (1 January 2015 to 31 December 2021). We defined two periods for pre- and post-COVID-19 restrictions implementation, corresponding to before and after the first UK-wide lockdown on 23 March 2020. We conducted a time series analysis, assessing differences in C. parvum and C. hominis incidence, trends and periodicity between these periods.Results. There were 21 304 cases (C. parvum=12 246; C. hominis=9058). Post-restrictions implementation incidence of C. hominis dropped by 97.5 % (95 % CI: 95.4-98.6 %; P<0.001). The decreasing incidence trend pre-restrictions was not observed post-restrictions implementation due to lack of cases. No periodicity change was observed post-restrictions implementation. There was a strong social gradient; there was a higher proportion of cases in deprived areas. For C. parvum, post-restrictions implementation incidence fell by 49.0 % (95 % CI: 38.4-58.3 %; P<0.001). There was no pre-restrictions incidence trend but an increasing incidence trend post-restrictions implementation. A periodicity change was observed post-restriction implementation, peaking 1 week earlier in spring and 2 weeks later in autumn. The social gradient was the inverse of that for C. hominis. Where recorded, 22 % of C. hominis and 8 % of C. parvum cases had travelled abroad.Conclusion. C. hominis cases almost entirely ceased post-restrictions implementation, reinforcing that foreign travel seeds infections. C. parvum incidence fell sharply but recovered post-restrictions implementation, consistent with relaxation of restrictions. Future exceedance reporting for C. hominis should exclude the post-restriction implementation period but retain it for C. parvum (except the first 6 weeks post-restrictions implementation). Infection prevention and control advice should be improved for people with gastrointestinal illness (GI) symptoms to ensure hand hygiene and swimming pool avoidance.

Quantitative Study of a Regional Patient Portal Usage in the Pandemic Period.

In 2013 using a Public Procurement of Innovation procedure the Region of Galicia developed a patient portal called "E-Saúde", that went live in 2015. COVID situation in 2019 produced a high demand of e-health services, scaling by 10x the number of users in 2021. OBJECTIVE: In this study a quantitative description of patient portal usage from 2018 to 2022 is made to show the behaviour of usage trends of a patient portal before, during and after COVID pandemic. METHODS: Two main data sets were obtained from patient portal logs to obtain: 1) Enrolment of new users and number of sessions opened in the portal. 2) Detailed usage of relevant functionalities. Descriptive statistical methods were applied to show the usage of the portal in a biannual time series description. RESULTS: Prior to the pandemic, the portal was gradually being introduced to citizens. During pandemics, more than 1 million users were registered and a peak of 15x usage could be observed. After COVID, the level of usage of portal services decreased, but kept a sustained trend five times higher than in Pre-COVID situation. CONCLUSION: There is limited information available on metrics, functionalities and acceptability for general purpose patient portals, but the analysis performed on usage levels shows that after a high peak reached during COVID period, explained by the need of direct access to clinical information, the level of usage of the patient portal remains five times higher than in pre-pandemic situation for all functionalities of the patient portal.

Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data setting.

INTRODUCTION: Older people were at particular risk of morbidity and mortality during COVID-19. Consequently, they experienced formal (externally imposed) and informal (self-imposed) periods of social isolation and quarantine. This is hypothesised to have led to physical deconditioning, new-onset disability and frailty. Disability and frailty are not routinely collated at population level but are associated with increased risk of falls and fractures, which result in hospital admissions. First, we will examine incidence of falls and fractures during COVID-19 (January 2020-March 2022), focusing on differences between incidence over time against expected rates based on historical data, to determine whether there is evidence of new-onset disability and frailty. Second, we will examine whether those with reported SARS-CoV-2 were at higher risk of falls and fractures. METHODS AND ANALYSIS: This study uses the Office for National Statistics (ONS) Public Health Data Asset, a linked population-level dataset combining administrative health records with sociodemographic data of the 2011 Census and National Immunisation Management System COVID-19 vaccination data for England. Administrative hospital records will be extracted based on specific fracture-centric International Classification of Diseases-10 codes in years preceding COVID-19 (2011-2020). Historical episode frequency will be used to predict expected admissions during pandemic years using time series modelling, if COVID-19 had not occurred. Those predicted admission figures will be compared with actual admissions to assess changes in hospital admissions due to public health measures comprising the pandemic response. Hospital admissions in prepandemic years will be stratified by age and geographical characteristics and averaged, then compared with pandemic year admissions to assess more granular changes. Risk modelling will assess risk of experiencing a fall, fracture or frail fall and fracture, if they have reported a positive case of COVID-19. The combination of these techniques will provide insight into changes in hospital admissions from the COVID-19 pandemic. ETHICS AND DISSEMINATION: This study has approval from the National Statistician's Data Ethics Advisory Committee (NSDEC(20)12). Results will be made available to other researchers via academic publication and shared via the ONS website.

Novel Trial Design: CHIEF-HF.

BACKGROUND: The expense of clinical trials mandates new strategies to efficiently generate evidence and test novel therapies. In this context, we designed a decentralized, patient-centered randomized clinical trial leveraging mobile technologies, rather than in-person site visits, to test the efficacy of 12 weeks of canagliflozin for the treatment of heart failure, regardless of ejection fraction or diabetes status, on the reduction of heart failure symptoms. METHODS: One thousand nine hundred patients will be enrolled with a medical record-confirmed diagnosis of heart failure, stratified by reduced (≤40%) or preserved (>40%) ejection fraction and randomized 1:1 to 100 mg daily of canagliflozin or matching placebo. The primary outcome will be the 12-week change in the total symptom score of the Kansas City Cardiomyopathy Questionnaire. Secondary outcomes will be daily step count and other scales of the Kansas City Cardiomyopathy Questionnaire. RESULTS: The trial is currently enrolling, even in the era of the coronavirus disease 2019 (COVID-19) pandemic. CONCLUSIONS: CHIEF-HF (Canagliflozin: Impact on Health Status, Quality of Life and Functional Status in Heart Failure) is deploying a novel model of conducting a decentralized, patient-centered, randomized clinical trial for a new indication for canagliflozin to improve the symptoms of patients with heart failure. It can model a new method for more cost-effectively testing the efficacy of treatments using mobile technologies with patient-reported outcomes as the primary clinical end point of the trial. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04252287.