Resurgence Of Cases Research Articles

Rebound in epidemic control: how misaligned vaccination timing amplifies infection peaks

In this study, we explore the dynamic interplay between the timing of vaccination campaigns and the trajectory of disease spread in a population. Through modeling and comprehensive data analysis of model output, we have uncovered a counter-intuitive phenomenon: initiating a vaccination process at an inopportune moment can paradoxically result in a more pronounced second peak of infections. This “rebound” phenomenon challenges the conventional understanding of vaccination impacts on epidemic dynamics. We provide a detailed examination of how improperly timed vaccination efforts can inadvertently reduce the overall immunity level in a population, considering both natural and vaccine-induced immunity. Our findings reveal that such a decrease in population-wide immunity can lead to a delayed, yet more severe, resurgence of cases. This study not only adds a critical dimension to our understanding of vaccination strategies in controlling pandemics but also underscores the necessity for strategically timed interventions to optimize public health outcomes. Furthermore, we compute which vaccination strategies are optimal for a COVID-19 tailored mathematical model, and find that there are two types of optimal strategies. The first type prioritizes vaccinating early and rapidly to reduce the number of deaths, while the second type acts later and more slowly to reduce the number of cases; both of them target primarily the elderly population. Our results hold significant implications for the formulation of vaccination policies, particularly in the context of rapidly evolving infectious diseases.

Transmission dynamics and effect of control measures on the 2022 outbreak of mpox among gay, bisexual, and other men who have sex with men in England: a mathematical modelling study

The 2022 global outbreak of mpox (formerly known as monkeypox) spread primarily among gay, bisexual, and other men who have sex with men (GBMSM), with the initial cluster being identified in England in May, 2022. Understanding its epidemiological characteristics and the reasons for its downturn in July, 2022, will help to control future outbreaks. We collated data for all diagnosed mpox cases (3621) from England from May 1, 2022, to Nov 16, 2022. Data from 75 individuals with mpox allowed estimation of the incubation period, while data from 121 case-contact pairs were used to estimate the serial interval. Six methods, including a structured dynamic compartmental transmission model, were used to estimate the basic reproduction number (R0). The structured model assumed all male individuals with mpox were GBMSM, who were then stratified into subgroups for those at low risk and high risk for mpox. This best fitting model was used to estimate the reduction in transmissibility, and the effective infectious period (before isolating), that resulted in the outbreak downturn, and the effect of vaccination initiated from June 27, 2022. Bayesian methods were used for parameter estimation and model calibration. Most cases occurred in men (3544 of 3621, 97·9%). The median incubation period for mpox was 6·90 days (95% credible interval [CrI] 4·08-20·21), and the serial interval was 8·82 days (5·22-25·81). R0 estimates ranged from 1·41 to 2·17. The structured transmission model estimated that 83·8% of infections (95% CrI 83·5-85·3) resulted from sexual partnerships with GBMSM individuals at high risk of mpox. The outbreak downturn probably resulted from a 44·5% reduction in the sexual partner rate among all GBMSM (24·9-55·8) and 20·0% reduction in the effective infectious period (4·1-33·9), preventing 165 896 infections (115 584-217 730). Vaccination marginally increased the number of infections prevented (166 081, 115 745-217 947), but minimised a resurgence in cases from January, 2023, and could have averted four times more infections if initiated earlier. Our findings were sensitive to assumptions regarding the vaccine's effectiveness and the GBMSM subgroup at high risk of mpox. The mpox outbreak in England probably resulted from high sexual partner rates among some GBMSM, with reductions in partner rates reversing the outbreak, and with vaccination minimising future outbreaks. National Institute for Health Research (UK).

The relative effect of climate variability on malaria incidence after scale-up of interventions in western Kenya: A time-series analysis of monthly incidence data from 2008 to 2019

BackgroundDespite considerable progress made over the past 20 years in reducing the global burden of malaria, the disease remains a major public health problem and there is concern that climate change might expand suitable areas for transmission. This study investigated the relative effect of climate variability on malaria incidence after scale-up of interventions in western Kenya. MethodsBayesian negative binomial models were fitted to monthly malaria incidence data, extracted from records of patients with febrile illnesses visiting the Lwak Mission Hospital between 2008 and 2019. Data pertaining to bed net use and socio-economic status (SES) were obtained from household surveys. Climatic proxy variables obtained from remote sensing were included as covariates in the models. Bayesian variable selection was used to determine the elapsing time between climate suitability and malaria incidence. ResultsMalaria incidence increased by 50% from 2008 to 2010, then declined by 73% until 2015. There was a resurgence of cases after 2016, despite high bed net use. Increase in daytime land surface temperature was associated with a decline in malaria incidence (incidence rate ratio [IRR] = 0.70, 95% Bayesian credible interval [BCI]: 0.59–0.82), while rainfall was associated with increased incidence (IRR = 1.27, 95% BCI: 1.10–1.44). Bed net use was associated with a decline in malaria incidence in children aged 6–59 months (IRR = 0.78, 95% BCI: 0.70–0.87) but not in older age groups, whereas SES was not associated with malaria incidence in this population. ConclusionsVariability in climatic factors showed a stronger effect on malaria incidence than bed net use. Bed net use was, however, associated with a reduction in malaria incidence, especially among children aged 6–59 months after adjusting for climate effects. To sustain the downward trend in malaria incidence, this study recommends continued distribution and use of bed nets and consideration of climate-based malaria early warning systems when planning for future control interventions.

1067. Predicting next 7-day Discharges of Hospitalized COVID-19 Patients Using Ensemble Learning

Abstract Background COVID-19 pandemic, especially during resurgences of cases in hard-hit areas, led to significant shortage of hospital beds. Such shortages may be alleviated through timely and effective forecasting of hospital discharges. The objective of this study is to predict next 7-day discharges of hospitalized COVID-19 patients using daily-based electronic health records (EHR) data. Methods Using EHR data of hospitalized COVID-19 patients from 03/2020-08/2021, we employed ensemble learning to predict next 7-day discharges of individual patients. We used both baseline and daily inpatient features for model training, validation, and test. Baseline features include demographic and clinical characteristics, and comorbidities. The daily inpatient features were vital signs, laboratory tests, medications administered, acute physiological scores, use of ventilator, and use of intensive care unit. 1832 hospitalized patients were identified (12,397 hospital days). Samples were randomly split at patient level (7:2:1) into training set (N=1,283 patients with 8,704 hospital days), validation set (N=366 patients with 2,524 days), and test/holdout set (patient N=183, and 1,169 days). Prediction models were trained on the training set and the validation set. We conducted the model training separately on the samples of admission day and the samples of days after admission day. The predictions were based on the ensemble learning from decision tree, XGBoost, logistic regression, and multilayer perceptron, long short-term memory (LSTM), bi-directional LSTM, and convolutional neural network. The combination of ensemble learning on the test/holdout set was used for final next 7-day predictions based on ‘hard’ voting (by majority). Where there was a tie, we used ‘soft’ voting (sum of probabilities) to break the tie. Figure 1.Data Processing PipelineFigure 2.Ensemble Model Architecture Results The overall average hospital length of stay was 8.7 (SD=10.5) days. The ensemble learning accuracies for admission-day samples and after-admission-day samples were 0.781 and 0.793, and the F1-scores for were 0.761 and 0.789, respectively. Conclusion EHR data of hospitalized COVID-19 patients can be used to predict next 7-day hospital discharges. Additional inpatient features and more advanced machine learning techniques are needed for prediction accuracy improvement. Disclosures All Authors: No reported disclosures.

COVID-19 endgame: From pandemic to endemic? Vaccination, reopening and evolution in low- and high-vaccinated populations

COVID-19 remains a major public health concern, with large resurgences even where there has been widespread uptake of vaccines. Waning immunity and the emergence of new variants will shape the long-term burden and dynamics of COVID-19. We explore the transition to the endemic state, and the endemic incidence in British Columbia (BC), Canada and South Africa (SA), to compare low and high vaccination coverage settings with differing public health policies, using a combination of modelling approaches. We compare reopening (relaxation of public health measures) gradually and rapidly as well as at different vaccination levels. We examine how the eventual endemic state depends on the duration of immunity, the rate of importations, the efficacy of vaccines and the transmissibility. These depend on the evolution of the virus, which continues to undergo selection. Slower reopening leads to a lower peak level of incidence and fewer overall infections in the wave following reopening: as much as a 60% lower peak and a 10% lower total in some illustrative simulations; under realistic parameters, reopening when 70% of the population is vaccinated leads to a large resurgence in cases. The long-term endemic behaviour may stabilize as late as January 2023, with further waves of high incidence occurring depending on the transmissibility of the prevalent variant, duration of immunity, and antigenic drift. We find that long term endemic levels are not necessarily lower than current pandemic levels: in a population of 100,000 with representative parameter settings (Reproduction number 5, 1-year duration of immunity, vaccine efficacy at 80% and importations at 3 cases per 100K per day) there are over 100 daily incident cases in the model. Predicted prevalence at endemicity has increased more than twofold after the emergence and spread of Omicron. The consequent burden on health care systems depends on the severity of infection in immunized or previously infected individuals.

Infectious Disease Modeling with Socio-Viral Behavioral Aspects—Lessons Learned from the Spread of SARS-CoV-2 in a University

When it comes to understanding the spread of COVID-19, recent studies have shown that pathogens can be transmitted in two ways: direct contact and airborne pathogens. While the former is strongly related to the distancing behavior of people in society, the latter are associated with the length of the period in which the airborne pathogens remain active. Considering those facts, we constructed a compartmental model with a time-dependent transmission rate that incorporates the two sources of infection. This paper provides an analytical and numerical study of the model that validates trivial insights related to disease spread in a responsive society. As a case study, we applied the model to the COVID-19 spread data from a university environment, namely, the Institut Teknologi Bandung, Indonesia, during its early reopening stage, with a constant number of students. The results show a significant fit between the rendered model and the recorded cases of infections. The extrapolated trajectories indicate the resurgence of cases as students’ interaction distance approaches its natural level. The assessment of several strategies is undertaken in this study in order to assist with the school reopening process.

173 Leveraging Syndromic Surveillance Data to Create Emergency Department COVID19 Data Visualization Tool

173 Leveraging Syndromic Surveillance Data to Create Emergency Department COVID19 Data Visualization Tool

Optimal health and economic impact of non-pharmaceutical intervention measures prior and post vaccination in England: a mathematical modelling study.

Background. Even with good progress on vaccination, SARS-CoV-2 infections in the UK may continue to impose a high burden of disease and therefore pose substantial challenges for health policy decision makers. Stringent government-mandated physical distancing measures (lockdown) have been demonstrated to be epidemiologically effective, but can have both positive and negative economic consequences. The duration and frequency of any intervention policy could, in theory, be optimized to maximize economic benefits while achieving substantial reductions in disease. Methods. Here, we use a pre-existing SARS-CoV-2 transmission model to assess the health and economic implications of different strengths of control through time in order to identify optimal approaches to non-pharmaceutical intervention stringency in the UK, considering the role of vaccination in reducing the need for future physical distancing measures. The model is calibrated to the COVID-19 epidemic in England and we carry out retrospective analysis of the optimal timing of precautionary breaks in 2020 and the optimal relaxation policy from the January 2021 lockdown, considering the willingness to pay (WTP) for health improvement. Results. We find that the precise timing and intensity of interventions is highly dependent upon the objective of control. As intervention measures are relaxed, we predict a resurgence in cases, but the optimal intervention policy can be established dependent upon the WTP per quality adjusted life year loss avoided. Our results show that establishing an optimal level of control can result in a reduction in net monetary loss of billions of pounds, dependent upon the precise WTP value. Conclusion. It is vital, as the UK emerges from lockdown, but continues to face an on-going pandemic, to accurately establish the overall health and economic costs when making policy decisions. We demonstrate how some of these can be quantified, employing mechanistic infectious disease transmission models to establish optimal levels of control for the ongoing COVID-19 pandemic.

COVID-19 Vaccination Status, Attitudes, and Values among US Adults in September 2021.

Background: The Delta COVID-19 variant caused a resurgence in cases and deaths during the summer of 2021, particularly among the unvaccinated, highlighting the need to increase vaccine coverage. We describe a survey conducted in September 2021, in the midst of the Delta variant surge, after the FDA fully approved Pfizer-BioNTech’s vaccine for ages 16+ and issued an emergency use authorization for ages 12–15. Methods and Findings: US adults were surveyed to measure COVID-19 vaccination status, intentions, attitudes, values, and trust in public health authorities. More than three-quarters (77%) reported receiving at least one dose of COVID-19 vaccination. Of the unvaccinated, 6% intended to vaccinate, 40% were unlikely to ever vaccinate, and 55% remained uncertain. Most of the unvaccinated were <45 years old (62%), without a bachelor’s degree (83%), earning less than $85,000 annually (74%), and Republican/Independent (66%). Concerns among the unvaccinated-yet-still-uncertain included the vaccines’ safety (86%), speed of development (86%), and suspicion of government (79%) and pharmaceutical companies (69%). Most (86%) of the unvaccinated reported they would not vaccinate if mandated by their employer. About one third (34%) of the unvaccinated reported facing at least one barrier to vaccination. Conclusion: More than half of unvaccinated adults remained uncertain about COVID-19 vaccination, indicating an opportunity to support their decision making. Public health must increase easy and equitable access to vaccination and renew efforts to provide unvaccinated populations access to information from trusted sources.

When Do Epidemics End? Scientific Insights from Mathematical Modelling Studies

Quantitative assessments of when infectious disease outbreaks end are crucial, as resources targeted towards outbreak responses typically remain in place until outbreaks are declared over. Recent improvements and innovations in mathematical approaches for determining when outbreaks end provide public health authorities with more confidence when making end-of-outbreak declarations. Although quantitative analyses of outbreaks have a long history, more complex mathematical and statistical methodologies for analysing outbreak data were developed early in the 20th century and continue to be refined. Historically, such methodologies focused primarily on factors affecting the early and middle phases of an outbreak, with less attention given to determining how and when outbreaks end. This review discusses mathematical modelling methods from the last 20 years that have been developed for determining the ends of infectious disease outbreaks, and considers factors that affect the accuracy of such determinations. When disease surveillance systems provide timely and representative data to inform models, the timings of end-of-outbreak declarations can be fine-tuned to allow outbreaks to be declared over quickly and with a low risk of being incorrect. Premature declarations that outbreaks are over can undermine earlier achievements in disease control and may result in a resurgence of cases, but unnecessary delays in declaring outbreaks over can cause significant economic and social harm. Appropriate declarations that balance the benefits of relaxing control measures against the risk of a surge in cases allow public health resources to be conserved (and economic and social pressures to be reduced) while limiting the potential for additional transmission.

Intention to vaccinate against COVID-19 and adherence to non-pharmaceutical interventions against COVID-19 prior to the second wave of the pandemic in Uganda: a cross-sectional study

ObjectivesThe resurgence in cases and deaths due to COVID-19 in many countries suggests complacency in adhering to COVID-19 preventive guidelines. Vaccination, therefore, remains a key intervention in mitigating the impact...

Impacts of a delayed and slow-paced vaccination on cases and deaths during the COVID-19 pandemic: a modelling study.

In Brazil, vaccination has always cut across party political and ideological lines, which has delayed its start and brought the whole process into disrepute. Such divergences put the immunization of the population in the background and create additional hurdles beyond the pandemic, mistrust and scepticism over vaccines. We conduct a mathematical modelling study to analyse the impacts of late vaccination along with slowly increasing coverage, as well as how harmful it would be if part of the population refused to get vaccinated or missed the second dose. We analyse data from confirmed cases, deaths and vaccination in the state of Rio de Janeiro in the period between 10 March 2020 and 27 October 2021. We estimate that if the start of vaccination had been 30 days earlier, combined with efforts to drive vaccination rates up, about 31 657 deaths could have been avoided. In addition, the slow pace of vaccination and the low demand for the second dose could cause a resurgence of cases as early as 2022. Even when reaching the expected vaccination coverage for the first dose, it is still challenging to increase adherence to the second dose and maintain a high vaccination rate to avoid new outbreaks.

A blend of microencapsulated organic acids and botanicals reduces necrotic enteritis via specific signaling pathways in broilers

Necrotic enteritis (NE) is a devastating disease that has seen a resurgence of cases following the removal of antibiotics from feed resulting in financial loss and significant animal health concerns across the poultry industry. The objective was to evaluate the efficacy of a microencapsulated blend of organic (25% citric and 16.7% sorbic) acids and botanicals (1.7% thymol and 1% vanillin [AviPlusP]) to reduce clinical NE and determine the signaling pathways associated with any changes. Day-of-hatch by-product broiler breeder chicks were randomly assigned to a control (0) or supplemented (500 g/MT) diet (n = 23–26) and evaluated in a NE challenge model (n = 3). Birds were administered 2X cocci vaccine on d 14 and challenged with a cocktail of Clostridium perfringens strains (107) on d 17 to 19. On d 20 to 21 birds were weighed, euthanized, and scored for NE lesions. Jejunal tissue was collected for kinome analysis using an immuno-metabolism peptide array (n = 5; 15/treatment) to compare tissue from supplement-fed birds to controls. Mortality and weight were analyzed using Student's t test and lesion scores analyzed using F-test two-sample for variances (P < 0.05). The kinome data was analyzed using PIIKA2 peptide array analysis software and fold-change between control and treated groups determined. Mortality in the supplemented group was 47.4% and 70.7% in controls (P = 0.004). Lesions scores were lower (P = 0.006) in supplemented birds (2.47) compared to controls (3.3). Supplement-fed birds tended (P = 0.19) to be heavier (848.6 g) than controls (796.2 g). Kinome analysis showed T cell receptor, TNF and NF-kB signaling pathways contributed to the improvements seen in the supplement-fed birds. The following peptides were significant (P < 0.05) in all 3 pathways: CHUK, MAP3K14, MAP3K7, and NFKB1 indicating their importance. Additionally, there were changes to IL6, IL10, and IFN- γ mRNA expression in tissue between control- and supplement-fed chickens. In conclusion, the addition of a microencapsulated blend of organic acids and botanicals to a broiler diet reduced the clinical signs of NE that was mediated by specific immune-related pathways.

Pandemic response credit-claiming and blame-avoidance in France

Abstract Credit claiming led in France during the first wave to centralization and during the summer to decentralization. During the second wave, blame-avoidance led again to centralization. First wave: In the spring, the French government attempted to take credit by centralizing the crisis governance but soon faced mounting criticism from the population, health care professionals and members of the political opposition. These initial missteps prompted legislators to set up two parliamentary inquiry commissions. Complaints were filed against several members of government, including former Prime Minister Edouard Philippe and former Health Minister Agnès Buzyn. In July, Phillipe was replaced by Jean Castex, who was tasked with designing France's reopening strategy with greater attention to regional needs. Summer: The government's response to Covid-19 significantly changed during the summer. The government's failure to put in place a critical triptych of testing, tracing and isolation and to contain the spread of the virus led to a recentralization of the crisis governance and a second national lockdown in late October. Second wave: Although the first lockdown was deemed “necessary” by most French people, implementation of stringent measures was less accepted by the population after a resurgence of cases at the end of the summer. As France entered a third lockdown in late March 2021, Macron's popularity rate fell 4 percentage point from a month earlier. According to an IFOP poll, 37% people said they were satisfied with the president's management of the pandemic.

Interview With Shu-Ti Chiou About Taiwan

After successfully eliminating the virus from its territory for many months, in May 2021, Taiwan faced a rapid resurgence in cases. The vaccine coverage rate was extremely low at that time. The health system was rapidly overwhelmed, and the case fatality rate reached one of the highest in the world. The alert level, after tremendous … Continued

Children should be offered vaccination against COVID-19

Since the start of the COVID-19 pandemic, there has been conflicting evidence on SARS-CoV-2 infection and transmission in children. Early studies reported only anecdotal outbreaks in school settings and low case numbers in children, driving speculation that the virus may not be as easily spread in this age group. However, these reports are unlikely to have represented the true frequency of infections, given the widespread school closures implemented to cut transmission opportunities and limitations of swab testing in children (lower uptake, swab volumes) resulting in missed cases. Indeed, subsequent studies measuring viral load in children reveal similar levels and trajectories as adults, indicating that children can readily transmit the virus and can accelerate infections throughout communities. In the midst of a fourth COVID-19 wave and a resurgence of cases in Canada, the majority with the highly transmissible and virulent B.1.617.2 (delta) variant, we discuss the pressing need for vaccination of children.

COVID-19: How Can Doulas Support Pandemic Control?

COVID-19 represents a great threat to public health in the 21st century so far, with the maternal and child (MCH) population being particularly vulnerable. With the healthcare workforce getting overwhelmed by a resurgence of cases, task-shifting approaches are a viable option to address the acute shortage of personnel for epidemic intelligence assignments related to the COVID-19 pandemic. We propose an intensive and short-duration curriculum to train Doulas versed in MCH epidemic intelligence and capable of reducing the burden of COVID-19 and its consequences on the MCH population. The effectiveness of the proposed curriculum will be monitored using a rapid-cycle evaluative approach to ascertain progressive enhancement over time. Copyright © 2021 Maiyegun, et al. Published by Global Health and Education Projects, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in this journal, is properly cited.

Social Intervention by the Numbers: Evidence Behind the Specific Public Health Guidelines in the COVID-19 Pandemic.

Social Intervention by the Numbers: Evidence Behind the Specific Public Health Guidelines in the COVID-19 Pandemic.

COVID-19: A Comprehensive Review of Epidemiology and Public Health System Response in Nordic Region.

This paper investigates the epidemiology and public health response of novel coronavirus infection (COVID-19) in the Nordic region. The data on cases and deaths due to COVID-19 were drawn from the European Centre for Disease Prevention and Control. The data on age- and sex-wise cases, deaths and intensive care unit (ICU) admissions, and public health interventions in the Nordic region through November 10, 2020, were obtained from respective countries' health ministries. Sweden accounted for 60.59% of cases (162 240 of 267 768 cases) and 81% of deaths (6057 of 7477 cases) in the Nordic region. The incidence rate for the Nordic region was 989.59 per 100 000, varying from 327.30 per 100 000 in Finland to 1616.51 per 100 000 in Sweden, and the mortality rate for the region was 27.63 per 100 000, ranging from 5.3 per 100 000 in Norway to 60.35 per 100 000 in Sweden. The case-fatality ratio of the Nordic region was 2.79%. Females were more susceptible to COVID-19 infection than males (52.30% vs 47.66%), while males had a greater proportion of deaths (54.7%) and ICU need (71.99%) than females. It is imperative to continue with social distancing, mandatory masks, testing, prohibition of mass gatherings, isolation of confirmed cases, and preventing the importation of cases from other countries to avoid the further resurgence of cases.

Description of a Multi-faceted COVID-19 Pandemic Physician Workforce Plan at a Multi-site Academic Health System

BackgroundThe evolving COVID-19 pandemic has and continues to present a threat to health system capacity. Rapidly expanding an existing acute care physician workforce is critical to pandemic response planning in large urban academic health systems.InterventionThe Medical Emergency-Pandemic Operations Command (MEOC)—a multi-specialty team of physicians, operational leaders, and support staff within an academic Department of Medicine in Calgary, Canada—partnered with its provincial health system to rapidly develop a comprehensive, scalable pandemic physician workforce plan for non-ventilated inpatients with COVID-19 across multiple hospitals. The MEOC Pandemic Plan comprised seven components, each with unique structure and processes.MethodsIn this manuscript, we describe MEOC’s Pandemic Plan that was designed and implemented from March to May 2020 and re-escalated in October 2020. We report on the plan’s structure and process, early implementation outcomes, and unforeseen challenges. Data sources included MEOC documents, health system, public health, and physician engagement implementation data.Key ResultsFrom March 5 to October 26, 2020, 427 patients were admitted to COVID-19 units in Calgary hospitals. In the initial implementation period (March–May 2020), MEOC communications reached over 2500 physicians, leading to 1446 physicians volunteering to provide care on COVID-19 units. Of these, 234 physicians signed up for hospital shifts, and 227 physicians received in-person personal protective equipment simulation training. Ninety-three physicians were deployed on COVID-19 units at four large acute care hospitals. The resurgence of cases in September 2020 has prompted re-escalation including re-activation of COVID-19 units.ConclusionsMEOC leveraged an academic health system partnership to rapidly design, implement, and refine a comprehensive, scalable COVID-19 acute care physician workforce plan whose components are readily applicable across jurisdictions or healthcare crises. This description may guide other institutions responding to COVID-19 and future health emergencies.