scholarly journals Determinants of RSV epidemiology following suppression through pandemic contact restrictions

2021 ◽  
Author(s):  
Mihaly Koltai ◽  
Fabienne Krauer ◽  
David Hodgson ◽  
Edwin van Leeuwen ◽  
Marina Treskova-Schwarzbach ◽  
...  
Keyword(s):  
Mitigation Measures ◽  
Transmission Model ◽  
Temporary Increase ◽  
Previous Exposure ◽  
Dynamic Transmission Model ◽  
Contact Frequency ◽  
Age Structured ◽  
Immune Maturation ◽  
The Impact ◽  
Pharmaceutical Interventions

Introduction COVID-19 related non-pharmaceutical interventions (NPIs) led to a suppression of RSV circulation in winter 2020/21 throughout Europe and an off-season resurgence in Summer 2021 in several European countries. We explore how such temporary interruption may shape future RSV epidemiology and what factors drive the associated uncertainty. Methods We developed an age-structured dynamic transmission model to simulate pre-pandemic RSV infections and hospitalisations. We sampled parameters governing RSV seasonality, immunity acquisition and duration of post-infection immunity and retained those simulations that qualitatively fit the UK's pre-pandemic epidemiology. From Spring 2020 to Summer 2021 we assumed a 50% reduced contact frequency, returning to pre-pandemic levels from mid-May 2021. We simulated transmission forwards until 2023 and evaluated the impact of the sampled parameters on the projected trajectories of RSV hospitalisations. Results Following a lifting of contact restrictions in summer 2021 the model replicated an out-of-season resurgence of RSV. If unmitigated, paediatric RSV hospitalisation incidence in the 2021/22 season was projected to increase by 32% to 67% compared to pre-pandemic levels. The size of the increase depended most on whether infection risk was primarily determined by immunity acquired from previous exposure or general immune maturation. While infants were less affected, the increase in seasonal hospitalisation incidence exceeded 100% in 1-2 year old children and 275% in 2-5 year old children, respectively, in some simulations where immunity from previous exposure dominated. Consequently, the average age of a case increased by 1 to 5 months, most markedly if there was strong immunity acquisition from previous exposure. If immunity to infection was largely determined by age rather than previous exposure, the 2021/22 season started earlier and lasted longer but with a peak incidence lower or similar to pre-pandemic levels. For subsequent seasons, simulations suggested a quick return to pre-pandemic epidemiology, with some slight oscillating behaviour possible depending on the strength of post-exposure immunity. Conclusion COVID-19 mitigation measures stopped RSV circulation in the 2020/21 season and generated immunity debt that will likely lead to a temporary increase in RSV burden in the season following the lifting of restrictions, particularly in 1 to 5 year old children. A more accurate understanding of immunity drivers for RSV is needed to better predict the size of such an increase and plan a potential expansion of pharmaceutical and non-pharmaceutical mitigation measures.

scholarly journals The effect of non-pharmaceutical interventions on COVID-19 cases, deaths and demand for hospital services in the UK: a modelling study

2020 ◽  
Author(s):  
Nicholas G. Davies ◽  
Adam J. Kucharski ◽  
Rosalind M. Eggo ◽  
Amy Gimma ◽  
W. John Edmunds ◽  
...  
Keyword(s):  
Intensive Care ◽  
Healthcare System ◽  
Control Measures ◽  
Transmission Model ◽  
School Closures ◽  
Social Distancing ◽  
Age Structured ◽  
The Uk ◽  
The Impact ◽  
Pharmaceutical Interventions

AbstractBackgroundNon-pharmaceutical interventions have been implemented to reduce transmission of SARS-CoV-2 in the UK. Projecting the size of an unmitigated epidemic and the potential effect of different control measures has been critical to support evidence-based policymaking during the early stages of the epidemic.MethodsWe used a stochastic age-structured transmission model to explore a range of intervention scenarios, including the introduction of school closures, social distancing, shielding of elderly groups, self-isolation of symptomatic cases, and extreme “lockdown”-type restrictions. We simulated different durations of interventions and triggers for introduction, as well as combinations of interventions. For each scenario, we projected estimated new cases over time, patients requiring inpatient and critical care (intensive care unit, ICU) treatment, and deaths.FindingsWe found that mitigation measures aimed at reducing transmission would likely have decreased the reproduction number, but not sufficiently to prevent ICU demand from exceeding NHS availability. To keep ICU bed demand below capacity in the model, more extreme restrictions were necessary. In a scenario where “lockdown”-type interventions were put in place to reduce transmission, these interventions would need to be in place for a large proportion of the coming year in order to prevent healthcare demand exceeding availability.InterpretationThe characteristics of SARS-CoV-2 mean that extreme measures are likely required to bring the epidemic under control and to prevent very large numbers of deaths and an excess of demand on hospital beds, especially those in ICUs.Research in ContextEvidence before this studyAs countries have moved from early containment efforts to planning for the introduction of large-scale non-pharmaceutical interventions to control COVID-19 outbreaks, epidemic modelling studies have explored the potential for extensive social distancing measures to curb transmission. However, it remains unclear how different combinations of interventions, timings, and triggers for the introduction and lifting of control measures may affect the impact of the epidemic on health services, and what the range of uncertainty associated with these estimates would be.Added value of this studyUsing a stochastic, age-structured epidemic model, we explored how eight different intervention scenarios could influence the number of new cases and deaths, as well as intensive care beds required over the projected course of the epidemic. We also assessed the potential impact of local versus national targeting of interventions, reduction in leisure events, impact of increased childcare by grandparents, and timing of triggers for different control measures. We simulated multiple realisations for each scenario to reflect uncertainty in possible epidemic trajectories.Implications of all the available evidenceOur results support early modelling findings, and subsequent empirical observations, that in the absence of control measures, a COVID-19 epidemic could quickly overwhelm a healthcare system. We found that even a combination of moderate interventions – such as school closures, shielding of older groups and self-isolation – would be unlikely to prevent an epidemic that would far exceed available ICU capacity in the UK. Intermittent periods of more intensive lockdown-type measures are predicted to be effective for preventing the healthcare system from being overwhelmed.

scholarly journals Analysis and Evaluation of Non-Pharmaceutical Interventions on Prevention and Control of COVID-19: A Case Study of Wuhan City

2021 ◽  
Vol 10 (7) ◽  
pp. 480
Author(s):  
Wen Cao ◽  
Haoran Dai ◽  
Jingwen Zhu ◽  
Yuzhen Tian ◽  
Feilin Peng
Keyword(s):  
Prevention And Control ◽  
Transmission Model ◽  
Model Parameters ◽  
Protection Measures ◽  
Dynamic Transmission Model ◽  
Sufficient Intensity ◽  
And Control ◽  
Self Protection ◽  
The Impact ◽  
Pharmaceutical Interventions

As the threat of COVID-19 increases, many countries have carried out various non-pharmaceutical interventions. Although many studies have evaluated the impact of these interventions, there is a lack of mapping between model parameters and actual geographic areas. In this study, a non-pharmaceutical intervention model of COVID-19 based on a discrete grid is proposed from the perspective of geography. This model can provide more direct and effective information for the formulation of prevention and control policies. First, a multi-level grid was introduced to divide the geographical space, and the properties of the grid boundary were used to describe the quarantine status and intensity in these different spaces; this was also combined with the model of hospital isolation and self-protection. Then, a process for the spatiotemporal evolution of the early COVID-19 spread is proposed that integrated the characteristics of residents’ daily activities. Finally, the effect of the interventions was quantitatively analyzed by the dynamic transmission model of COVID-19. The results showed that quarantining is the most effective intervention, especially for infectious diseases with a high infectivity. The introduction of a quarantine could effectively reduce the number of infected humans, advance the peak of the maximum infected number of people, and shorten the duration of the pandemic. However, quarantines only function properly when employed at sufficient intensity; hospital isolation and self-protection measures can effectively slow the spread of COVID-19, thus providing more time for the relevant departments to prepare, but an outbreak will occur again when the hospital reaches full capacity. Moreover, medical resources should be concentrated in places where there is the most urgent need under a strict quarantine measure.

scholarly journals Model-based evaluation of school- and non-school-related measures to control the COVID-19 pandemic

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ganna Rozhnova ◽  
Christiaan H. van Dorp ◽  
Patricia Bruijning-Verhagen ◽  
Martin C. J. Bootsma ◽  
Janneke H. H. M. van de Wijgert ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Additional Benefit ◽  
Transmission Model ◽  
Time Points ◽  
School Based ◽  
Admission Data ◽  
Age Structured ◽  
The Impact ◽  
Pandemic Wave

AbstractThe role of school-based contacts in the epidemiology of SARS-CoV-2 is incompletely understood. We use an age-structured transmission model fitted to age-specific seroprevalence and hospital admission data to assess the effects of school-based measures at different time points during the COVID-19 pandemic in the Netherlands. Our analyses suggest that the impact of measures reducing school-based contacts depends on the remaining opportunities to reduce non-school-based contacts. If opportunities to reduce the effective reproduction number (Re) with non-school-based measures are exhausted or undesired and Re is still close to 1, the additional benefit of school-based measures may be considerable, particularly among older school children. As two examples, we demonstrate that keeping schools closed after the summer holidays in 2020, in the absence of other measures, would not have prevented the second pandemic wave in autumn 2020 but closing schools in November 2020 could have reduced Re below 1, with unchanged non-school-based contacts.

scholarly journals The effects of non-pharmaceutical interventions on SARS-CoV-2 transmission in different socioeconomic populations in Kuwait: a modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fatima Khadadah ◽  
Abdullah A. Al-Shammari ◽  
Ahmad Alhashemi ◽  
Dari Alhuwail ◽  
Bader Al-Saif ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Reproduction Number ◽  
Transmission Model ◽  
Socioeconomic Groups ◽  
Before And After ◽  
Cross Transmission ◽  
Community Transmission ◽  
The Impact ◽  
Pharmaceutical Interventions ◽  
The Basic Reproduction Number

Abstract Background Aggressive non-pharmaceutical interventions (NPIs) may reduce transmission of SARS-CoV-2. The extent to which these interventions are successful in stopping the spread have not been characterized in countries with distinct socioeconomic groups. We compared the effects of a partial lockdown on disease transmission among Kuwaitis (P1) and non-Kuwaitis (P2) living in Kuwait. Methods We fit a modified metapopulation SEIR transmission model to reported cases stratified by two groups to estimate the impact of a partial lockdown on the effective reproduction number ($$ {\mathcal{R}}_e $$ R e ). We estimated the basic reproduction number ($$ {\mathcal{R}}_0 $$ R 0 ) for the transmission in each group and simulated the potential trajectories of an outbreak from the first recorded case of community transmission until 12 days after the partial lockdown. We estimated $$ {\mathcal{R}}_e $$ R e values of both groups before and after the partial curfew, simulated the effect of these values on the epidemic curves and explored a range of cross-transmission scenarios. Results We estimate $$ {\mathcal{R}}_e $$ R e at 1·08 (95% CI: 1·00–1·26) for P1 and 2·36 (2·03–2·71) for P2. On March 22nd, $$ {\mathcal{R}}_e $$ R e for P1 and P2 are estimated at 1·19 (1·04–1·34) and 1·75 (1·26–2·11) respectively. After the partial curfew had taken effect, $$ {\mathcal{R}}_e $$ R e for P1 dropped modestly to 1·05 (0·82–1·26) but almost doubled for P2 to 2·89 (2·30–3·70). Our simulated epidemic trajectories show that the partial curfew measure greatly reduced and delayed the height of the peak in P1, yet significantly elevated and hastened the peak in P2. Modest cross-transmission between P1 and P2 greatly elevated the height of the peak in P1 and brought it forward in time closer to the peak of P2. Conclusion Our results indicate and quantify how the same lockdown intervention can accentuate disease transmission in some subpopulations while potentially controlling it in others. Any such control may further become compromised in the presence of cross-transmission between subpopulations. Future interventions and policies need to be sensitive to socioeconomic and health disparities.

scholarly journals Mathematical Models for Assessing Vaccination Scenarios in Several Provinces in Indonesia

2020 ◽  
Author(s):  
N. Nuraini ◽  
K. Khairudin ◽  
P. Hadisoemarto ◽  
H. Susanto ◽  
A. Hasan ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Age Groups ◽  
Transmission Model ◽  
West Java ◽  
Dynamic Transmission Model ◽  
Simulation Results ◽  
Age Structured

AbstractTo mitigate more casualties from the COVID-19 outbreak, this study assessed optimal vaccination scenarios, considering some existing healthcare conditions and some assumptions, by developing SIQRD (Susceptible-Infected-Quarantine-Recovery-Death) models for Jakarta, West Java, and Banten, in Indonesia. The models included an age-structured dynamic transmission model that naturally could give different treatments among age groups of population. The simulation results show that the timing and period’s length of the vaccination should be well planned and prioritizing particular age groups will give significant impact on the total number of casualties.

scholarly journals Model-based evaluation of school- and non-school-related measures to control the COVID-19 pandemic

2021 ◽  
Author(s):  
Ganna Rozhnova ◽  
Christiaan van Dorp ◽  
Patricia Bruijning-Verhagen ◽  
Martin Bootsma ◽  
Janneke van de Wijgert ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Additional Benefit ◽  
Transmission Model ◽  
Time Points ◽  
School Based ◽  
Admission Data ◽  
Age Structured ◽  
The Impact ◽  
Pandemic Wave

Abstract The role of school-based contacts in the epidemiology of SARS-CoV-2 is incompletely understood. We used an age-structured transmission model fitted to age-specific seroprevalence and hospital admission data to assess the effects of school-based measures at different time points during the COVID-19 pandemic in the Netherlands. Our analyses suggest that the impact of measures reducing school-based contacts depends on the remaining opportunities to reduce non-school-based contacts. If opportunities to reduce the effective reproduction number (Re) with non-school-based measures are exhausted or undesired and Re is still close to 1, the additional benefit of school-based measures may be considerable, particularly among older school children. As two examples, we demonstrate that keeping schools closed after the summer holidays in 2020, in the absence of other measures, would not have prevented the second pandemic wave in autumn 2020 but closing schools in November 2020 could have reduced Re below 1, with unchanged non-school-based contacts.

scholarly journals Impact of vaccination and non-pharmaceutical interventions on SARS-CoV-2 dynamics in Switzerland

2021 ◽  
Author(s):  
Andrew J. Shattock ◽  
Epke A. Le Rutte ◽  
Robert P Duenner ◽  
Swapnoleena Sen ◽  
Sherrie L Kelly ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Vaccination Coverage ◽  
Vaccination Campaign ◽  
Population Level ◽  
Morbidity And Mortality ◽  
Transmission Model ◽  
Third Wave ◽  
The Impact ◽  
Pharmaceutical Interventions

As vaccination coverage against SARS-CoV-2 increases amidst the emergence and spread of more infectious and potentially more deadly viral variants, decisions on timing and extent of relaxing effective, but unsustainable, non-pharmaceutical interventions (NPIs) need to be made. An individual-based transmission model of SARS-CoV-2 dynamics, OpenCOVID, was developed to compare the impact of various vaccination and NPI strategies on the COVID-19 epidemic in Switzerland. We estimate that any relaxation of NPIs in March 2021 will lead to increasing cases, hospitalisations, and deaths resulting in a "third wave" in spring and into summer 2021. However, we find a cautious phased relaxation can substantially reduce population-level morbidity and mortality. We find that faster vaccination campaign can offset the size of such a wave, allowing more flexibility for NPI to be relaxed sooner. Our sensitivity analysis revealed that model results are particularly sensitive to the infectiousness of variant B.1.1.7.

scholarly journals The effectiveness of interventions to reduce COVID-19 transmission in a large urban jail

2020 ◽  
Author(s):  
Giovanni S. P. Malloy ◽  
Lisa Puglisi ◽  
Margaret L. Brandeau ◽  
Tyler D. Harvey ◽  
Emily A. Wang
Keyword(s):  
Single Cells ◽  
Mitigation Strategies ◽  
Policy Implications ◽  
Transmission Model ◽  
Stochastic Dynamic ◽  
National Guidelines ◽  
Reproduction Ratio ◽  
Dynamic Transmission Model ◽  
Correctional Settings ◽  
The Impact

ABSTRACTObjectivesTo estimate the impact of various mitigation strategies on COVID-19 transmission in a U.S. jail beyond those offered in national guidelines.MethodsWe developed a stochastic dynamic transmission model of COVID-19 in one large urban U.S. jail among staff and incarcerated individuals. We divided the outbreak into four intervention phases: the start of the outbreak, depopulation of the jail, increased proportion of people in single cells, and asymptomatic testing. We used the next generation method to estimate the basic reproduction ratio, R0, in each phase. We estimated the fraction of new cases, hospitalizations, and deaths averted by these interventions along with the standard measures of sanitization, masking, and social distancing interventions.ResultsFor the first outbreak phase, the estimated R0 was 8.23 (95% CrI: 5.01-12.90), and for the subsequent phases, R0,phase 2 = 3.58 (95% CrI: 2.46-5.08), R0,phase 3 = 1.72 (95% CrI: 1.41-2.12), and R0,phase 4 = 0.45 (95% CrI: 0.32-0.59). In total, the jail’s interventions prevented approximately 83% of projected cases and hospitalizations and 89% of deaths over 83 days.ConclusionsDepopulation, single celling, and asymptomatic testing within jails can be effective strategies to mitigate COVID-19 transmission in addition to standard public health measures.Policy ImplicationsDecision-makers should prioritize reductions in the jail population, single celling, and testing asymptomatic populations, as additional measures to manage COVID-19 within correctional settings.

scholarly journals Modelling the impact of COVID-19-related programme interruptions on visceral leishmaniasis in India

2020 ◽  
Author(s):  
Epke A Le Rutte ◽  
Luc E Coffeng ◽  
Johanna Muñoz ◽  
Sake J de Vlas
Keyword(s):  
Public Health ◽  
Visceral Leishmaniasis ◽  
Health Problem ◽  
Public Health Problem ◽  
Mitigation Strategy ◽  
Mitigation Strategies ◽  
Transmission Model ◽  
Potential Impact ◽  
Age Structured ◽  
The Impact

AbstractBackgroundIn March 2020, India declared a nationwide lockdown to control the spread of COVID-19. As a result, control efforts against visceral leishmaniasis (VL) were interrupted.MethodsUsing an established age-structured deterministic VL transmission model, we predicted the impact of a 6 to 24-month programme interruption on the timeline towards achieving the VL elimination target, as well as on the increase of VL cases. We also explored the potential impact of a mitigation strategy after the interruption.ResultsDelays towards the elimination target are estimated to range between 0 to 9 years. Highly endemic settings where control efforts have been ongoing for 5-8 years are most affected by an interruption, for which we identified a mitigation strategy to be most relevant. However, more importantly, all settings can expect an increase in the number of VL cases. This increase is substantial even for settings with a limited expected delay in achieving the elimination target.ConclusionBesides implementing mitigation strategies, it is of great importance to try and keep the duration of the interruption as short as possible, to prevent new individuals from becoming infected with VL, and continue the efforts towards VL elimination as a public health problem in India.

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