scholarly journals Estimating the impact of low influenza activity in 2020 on population immunity and future influenza seasons in the United States

2021 ◽  
Author(s):  
Kyueun Lee ◽  
Hawre Jalal ◽  
Jonathan M Raviotta ◽  
Mary G Krauland ◽  
Richard K Zimmerman ◽  
...  
Keyword(s):  
Influenza Season ◽  
Vaccine Coverage ◽  
Transmission Rate ◽  
Influenza Infection ◽  
The United States ◽  
School Closure ◽  
Vaccine Uptake ◽  
Population Immunity ◽  
Influenza Activity ◽  
The Impact

Abstract Backgrounds Influenza activity in the 2020-21 season was remarkably low, likely due to implementation of public health preventive measures such as social distancing, mask-wearing, and school closure. With waning immunity, the impact of low influenza activity in the 2020-21 on the following season is unknown. Method We built a multi-strain compartmental model that captures immunity over multiple influenza seasons in the US. Compared to the counterfactual case, where influenza activity remained at the normal level in 2020-21, we estimated the change in the number of hospitalizations when the transmission rate was decreased by 20% in 2020-21. We varied the level of vaccine uptake and effectiveness in 2021-22. We measured the change in population immunity over time by varying the number of seasons with lowered influenza activity. Results With the lowered influenza activity in 2020-21, the model estimated 102,000 [95% CI: 57,000-152,000] additional hospitalizations in 2021-22, without changes in vaccine uptake and effectiveness. The estimated changes in hospitalizations varied depending on the level of vaccine uptake and effectiveness in the following year. Achieving 50% increase in vaccine coverage was necessary to avert the expected increase in hospitalization in the next influenza season. If the low influenza activity were to continue over several seasons, population immunity would remain low during those seasons, with 48% the population susceptible to influenza infection. Conclusion Our study projecteda large compensatory influenza season in 2021-22 due to a light season in 2020-21. However, higher influenza vaccine uptake would reduce this projected increase in influenza.

scholarly journals Predicting the impact of low influenza activity in 2020 on population immunity and future influenza season in the United States

2021 ◽  
Author(s):  
Kyueun Lee ◽  
Hawre Jalal ◽  
Jonathan M. Raviotta ◽  
Mary G. Krauland ◽  
Richard K. Zimmerman ◽  
...  
Keyword(s):  
Public Health ◽  
Vaccine Efficacy ◽  
Influenza Season ◽  
The United States ◽  
School Closure ◽  
Vaccine Uptake ◽  
Population Immunity ◽  
Influenza Activity ◽  
The Impact ◽  
Expected Increase

AbstractBackgroundsThe influenza season of 2020-21 was remarkably low, likely due to implementation of public health preventive measures such as social distancing, mask-wearing, and school closure and due to decreased international travel. This leads to a key public health question: what will happen in the 2021-22 influenza season? To answer this, we developed a multi-season influenza model that accounted for residual immunity from prior infection.MethodWe built a multi-strain, non-age structured compartmental model that captures immunity over multiple influenza seasons. By the end of the influenza season, we sorted the population based on their experience of natural infection and/or vaccination, which determines the susceptibility to influenza infection in the following season. Because the exact parameters of transmission rates and immunity are unknown, we implemented Bayesian calibration against the observed influenza epidemics (influenza hospitalization rates from 2012 to 2020 in the US) to estimate those parameters. In forward projections, we simulated low influenza activity in 2020-21 season by lowering transmission rate by 20%. Compared to the counterfactual case, in which influenza activity remained at the normal level in 2020-21, we estimated the change in the number of hospitalizations in the following seasons with varying level of vaccine uptake and effectiveness. We measured the change in population immunity over time by varying the number of seasons with low influenza activity.ResultWith the low influenza activity in 2020-21, the model estimated 102,000 [95% CI: 57,000-152,000] additional hospitalizations in 2021-22, without change in vaccine uptake and effectiveness. The expected change in hospitalization varied depending on the level of vaccine uptake and effectiveness in the following year. Achieving 50% increase in one of two measures (1.5X vaccine uptake with 1X vaccine efficacy or 1.5X vaccine efficacy with 1X vaccine uptake) was necessary to avert the expected increase in hospitalization in the next influenza season. Otherwise, increases in both measures by 25% averted the expected increase in influenza-hospitalization. If the low influenza activity seasons continue, population immunity would remain low during those seasons, with 48% the population susceptible to influneza infection.ConclusionWe predicted a large compensatory influenza season in 2021-2 due to a light season in 2020-21. However, higher influenza vaccine uptake would reduce this projected increase in influenza.

scholarly journals Agent-based Investigation of the Impact of Low Rates of Influenza on Next Season Influenza Infections

2021 ◽  
Author(s):  
Mary G Krauland ◽  
David D Galloway ◽  
Jonathan M Raviotta ◽  
Richard K Zimmerman ◽  
Mark S Roberts
Keyword(s):  
Young Children ◽  
Influenza Season ◽  
Vaccine Coverage ◽  
School Closure ◽  
Dynamics Simulation ◽  
Past Infection ◽  
Worst Case ◽  
Agent Based ◽  
Cross Immunity ◽  
The Impact

AbstractIntroductionInterventions to curb the spread of SARS-CoV-2 during the 2020-21 influenza season essentially eliminated influenza during that season. Given waning antibody titers over time, future residual population immunity against influenza will be reduced. The implication for the subsequent 2021-22 influenza season is unknown.MethodsWe used an agent-based model of influenza implemented in the FRED (Framework for Reconstructing Epidemiological Dynamics) simulation platform to estimate cases and hospitalization over two succeeding influenza seasons. The model uses a synthetic population to represent an actual population, and individual interactions in workplaces, school, households and neighborhoods. The impact of reduced residual immunity was estimated as a consequence of increased protective measures (e.g., social distancing and school closure) in the first season. The impact was contrasted by the level of similarity (cross-immunity) between influenza strains over the seasons.ResultsWhen the second season strains were dissimilar to the first season (have a low level of cross immunity), a low first season has limited impact on second season cases. When a high level of cross-immunity exists between strains in the 2 seasons, the first season has a much greater impact on the second season. In both cases this is modified by the transmissibility of strains in the 2 seasons. In the context of the 2021-22 season, the worst case scenario is a highly transmissible strain causing increased cases and hospitalizations over average influenza seasons, with a possible significant increase in cases in some scenarios. The most likely overall scenario for 2021-22 is a more modest increase in flu cases over an average season.DiscussionGiven the light 2020-21 season, we found that a large, compensatory second season might occur in 2021-22, depending on cross-immunity from past infection and transmissibility of strains. Furthermore, we found that enhanced vaccine coverage could reduce this high, compensatory season. Young children may be especially at risk in 2021-22 since very young children were unlikely to have had any exposure to infection and most immunity in that age group would be from vaccination, which wanes quickly.

scholarly journals Impact of Rapid PCR Influenza Testing on the Rate of Inpatient Admissions During Influenza Season at a Tertiary-Care Center

2020 ◽  
Vol 41 (S1) ◽  
pp. s263-s264
Author(s):  
Jordan Polistico ◽  
Avnish Sandhu ◽  
Teena Chopra ◽  
Erin Goldman ◽  
Jennifer LeRose ◽  
...  
Keyword(s):  
Influenza Season ◽  
Care Center ◽  
Tertiary Care ◽  
The United States ◽  
Turnaround Time ◽  
Care Hospital ◽  
Tertiary Care Center ◽  
Pediatric Hospital ◽  
Rapid Pcr ◽  
The Impact

Background: Influenza causes a high burden of disease in the United States, with an estimate of 960,000 hospitalizations in the 2017–2018 flu season. Traditional flu diagnostic polymerase chain reaction (PCR) tests have a longer (24 hours or more) turnaround time that may lead to an increase in unnecessary inpatient admissions during peak influenza season. A new point-of-care rapid PCR assays, Xpert Flu, is an FDA-approved PCR test that has a significant decrease in turnaround time (2 hours). The present study sought to understand the impact of implementing a new Xpert Flu test on the rate of inpatient admissions. Methods: A retrospective study was conducted to compare rates of inpatient admissions in patients tested with traditional flu PCR during the 2017–2018 flu season and the rapid flu PCR during the 2018–2019 flu season in a tertiary-care center in greater Detroit area. The center has 1 pediatric hospital (hospital A) and 3 adult hospitals (hospital B, C, D). Patients with influenza-like illness who presented to all 4 hospitals during 2 consecutive influenza seasons were analyzed. Results: In total, 20,923 patients were tested with either the rapid flu PCR or the traditional flu PCR. Among these, 14,124 patients (67.2%) were discharged from the emergency department and 6,844 (32.7%) were admitted. There was a significant decrease in inpatient admissions in the traditional flu PCR group compared to the rapid flu PCR group across all hospitals (49.56% vs 26.6% respectively; P < .001). As expected, a significant proportion of influenza testing was performed in the pediatric hospital, 10,513 (50.2%). A greater reduction (30% decrease in the rapid flu PCR group compared to the traditional flu PCR group) was observed in inpatient admissions in the pediatric hospital (Table 1) Conclusions: Rapid molecular influenza testing can significantly decrease inpatient admissions in a busy tertiary-care hospital, which can indirectly lead to improved patient quality with easy bed availability and less time spent in a private room with droplet precautions. Last but not the least, this testing method can certainly lead to lower healthcare costs.Funding: NoneDisclosures: None

scholarly journals Modeling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil

2021 ◽  
Author(s):  
Marcelo Eduardo Borges ◽  
Leonardo Souto Ferreira ◽  
Silas Poloni ◽  
Ângela Maria Bagattini ◽  
Caroline Franco ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Transmission Rate ◽  
Disease Incidence ◽  
Demographic Data ◽  
School Closure ◽  
Mitigation Measures ◽  
Contact Tracing ◽  
School Closures ◽  
Infection Transmission ◽  
The Impact

Among the various non–pharmaceutical interventions implemented in response to the Covid–19 pandemic during 2020, school closures have been in place in several countries to reduce infection transmission. Nonetheless, the significant short and long–term impacts of prolonged suspension of in–person classes is a major concern. There is still considerable debate around the best timing for school closure and reopening, its impact on the dynamics of disease transmission, and its effectiveness when considered in association with other mitigation measures. Despite the erratic implementation of mitigation measures in Brazil, school closures were among the first measures taken early in the pandemic in most of the 27 states in the country. Further, Brazil delayed the reopening of schools and stands among the countries in which schools remained closed for the most prolonged period in 2020. To assess the impact of school reopening and the effect of contact tracing strategies in rates of Covid–19 cases and deaths, we model the epidemiological dynamics of disease transmission in 3 large urban centers in Brazil under different epidemiological contexts. We implement an extended SEIR model stratified by age and considering contact networks in different settings – school, home, work, and elsewhere, in which the infection transmission rate is affected by various intervention measures. After fitting epidemiological and demographic data, we simulate scenarios with increasing school transmission due to school reopening. Our model shows that reopening schools results in a non–linear increase of reported Covid-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. While low rates of within[&ndash]school transmission resulted in small effects on disease incidence (cases/100,000 pop), intermediate or high rates can severely impact disease trends resulting in escalating rates of new cases even if other interventions remain unchanged. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects of reducing the total number of hospitalizations and deaths. Our results suggest that policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. Also, although contact tracing strategies are essential to prevent new infections and outbreaks within school environments, our data suggest that they are alone not sufficient to avoid significant impacts on community transmission in the context of school reopening in settings with high and sustained transmission rates.

scholarly journals A Community-Based Management of COVID-19 in a Mobile Container Unit

Vaccines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1362
Author(s):  
Elena Petrova ◽  
Timothy Farinholt ◽  
Tejas P. Joshi ◽  
Hannah Moreno ◽  
Mayar Al Mohajer ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
Vaccine Coverage ◽  
The United States ◽  
Vaccine Uptake ◽  
Vaccine Hesitancy ◽  
Air Filtration ◽  
Clinical Environment ◽  
Mobile Clinic ◽  
Community Based ◽  
Community Healthcare

Vaccine uptake is a multifactor measure of successful immunization outcomes that includes access to healthcare and vaccine hesitancy for both healthcare workers and communities. The present coronavirus disease (COVID-19) pandemic has highlighted the need for novel strategies to expand vaccine coverage in underserved regions. Mobile clinics hold the promise of ameliorating such inequities, although there is a paucity of studies that validate environmental infection in such facilities. Here, we describe community-based management of COVID-19 through a Smart Pod mobile clinic deployed in an underserved community area in the United States (Aldine, Harris County, TX, USA). In particular, we validate infection control and biological decontamination of the Smart Pod by testing surfaces and the air-filtration system for the COVID-19 virus and bacterial pathogens. We show the Smart Pod to be efficacious in providing a safe clinical environment for vaccine delivery. Moreover, in the Smart Pod, up-to-date education of community healthcare workers was provided to reduce vaccine hesitancy and improve COVID-19 vaccine uptake. The proposed solution has the potential to augment existing hospital capacity and combat the COVID-19 pandemic locally and globally.

scholarly journals Reactive school closure weakens the network of social interactions and reduces the spread of influenza

2019 ◽  
Vol 116 (27) ◽  
pp. 13174-13181 ◽  
Author(s):  
Maria Litvinova ◽  
Quan-Hui Liu ◽  
Evgeny S. Kulikov ◽  
Marco Ajelli
Keyword(s):  
Social Interactions ◽  
Influenza Season ◽  
School Closure ◽  
Transmission Model ◽  
Modeling Framework ◽  
School Closures ◽  
Student Absenteeism ◽  
Contact Survey ◽  
Closure Policy ◽  
The Impact

School-closure policies are considered one of the most promising nonpharmaceutical interventions for mitigating seasonal and pandemic influenza. However, their effectiveness is still debated, primarily due to the lack of empirical evidence about the behavior of the population during the implementation of the policy. Over the course of the 2015 to 2016 influenza season in Russia, we performed a diary-based contact survey to estimate the patterns of social interactions before and during the implementation of reactive school-closure strategies. We develop an innovative hybrid survey-modeling framework to estimate the time-varying network of human social interactions. By integrating this network with an infection transmission model, we reduce the uncertainty surrounding the impact of school-closure policies in mitigating the spread of influenza. When the school-closure policy is in place, we measure a significant reduction in the number of contacts made by students (14.2 vs. 6.5 contacts per day) and workers (11.2 vs. 8.7 contacts per day). This reduction is not offset by the measured increase in the number of contacts between students and nonhousehold relatives. Model simulations suggest that gradual reactive school-closure policies based on monitoring student absenteeism rates are capable of mitigating influenza spread. We estimate that without the implemented reactive strategies the attack rate of the 2015 to 2016 influenza season would have been 33% larger. Our study sheds light on the social mixing patterns of the population during the implementation of reactive school closures and provides key instruments for future cost-effectiveness analyses of school-closure policies.

Optimal public health intervention in a behavioural vaccination model: the interplay between seasonality, behaviour and latency period

2018 ◽  
Vol 36 (3) ◽  
pp. 297-324
Author(s):  
Bruno Buonomo ◽  
Rossella Della Marca ◽  
Alberto d’Onofrio
Keyword(s):  
Public Health ◽  
Side Effects ◽  
Perceived Risk ◽  
Transmission Rate ◽  
Minimum Principle ◽  
Public Health Intervention ◽  
Latency Period ◽  
Vaccine Uptake ◽  
Optimal Time ◽  
The Impact

AbstractHesitancy and refusal of vaccines preventing childhood diseases are spreading due to ‘pseudo-rational’ behaviours: parents overweigh real and imaginary side effects of vaccines. Nonetheless, the ‘Public Health System’ (PHS) may enact public campaigns to favour vaccine uptake. To determine the optimal time profiles for such campaigns, we apply the optimal control theory to an extension of the susceptible-infectious-removed (SIR)-based behavioural vaccination model by d’Onofrio et al. (2012, PLoS ONE, 7, e45653). The new model is of susceptible-exposed-infectious-removed (SEIR) type under seasonal fluctuations of the transmission rate. Our objective is to minimize the total costs of the disease: the disease burden, the vaccination costs and a less usual cost: the economic burden to enact the PHS campaigns. We apply the Pontryagin minimum principle and numerically explore the impact of seasonality, human behaviour and latency rate on the control and spread of the target disease. We focus on two noteworthy case studies: the low (resp. intermediate) relative perceived risk of vaccine side effects and relatively low (resp. very low) speed of imitation. One general result is that seasonality may produce a remarkable impact on PHS campaigns aimed at controlling, via an increase of the vaccination uptake, the spread of a target infectious disease. In particular, a higher amplitude of the seasonal variation produces a higher effort and this, in turn, beneficially impacts the induced vaccine uptake since the larger is the strength of seasonality, the longer the vaccine propensity remains large. However, such increased effort is not able to fully compensate the action of seasonality on the prevalence.

scholarly journals Critical care surveillance: insights into the impact of the 2010/11 influenza season relative to the 2009/10 pandemic season in England

2013 ◽  
Vol 18 (23) ◽  
Author(s):  
H K Green ◽  
J Ellis ◽  
M Galiano ◽  
J M Watson ◽  
R G Pebody
Keyword(s):  
Critical Care ◽  
Influenza A ◽  
Influenza Season ◽  
Severe Disease ◽  
Vaccine Uptake ◽  
Cold Weather ◽  
Influenza B ◽  
Influenza A H1n1 ◽  
The Impact ◽  
Age Shift

In 2010/11, the influenza season in England was marked by a relative increase in impact on the population compared to that seen during the 2009/10 pandemic, with the same influenza subtype, A(H1N1)pdm09, circulating. The peaks in critical care bed occupancy in both seasons coincided with peaks in influenza A(H1N1)pdm09 activity, but onset of influenza in 2010/11 additionally coincided with notably cold weather, a comparatively smaller peak in influenza B activity and increased reports of bacterial co-infection. A bigger impact on critical care services was seen across all regions in England in 2010/11, with, compared to 2009/10, a notable age shift in critical care admissions from children to young adults. The peak of respiratory syncytial virus (RSV) activity did not coincide with critical care admissions, and regression analysis suggested only a small proportion of critical care bed days might be attributed to the virus in either season. Differences in antiviral policy and improved overall vaccine uptake in 2010/11 with an influenza A(H1N1)pdm09 strain containing vaccine between seasons are unlikely to explain the change in impact observed between the two seasons. The reasons behind the relative high level of severe disease in the 2010/11 winter are likely to have resulted from a combination of factors, including an age shift in infection, accumulation of susceptible individuals through waning immunity, new susceptible individuals from new births and cold weather. The importance of further development of severe influenza disease surveillance schemes for future seasons is reinforced.

scholarly journals 1238Estimating the non-specific effects of seasonal influenza vaccine on RSV-hospitalisations in children

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Huong Le ◽  
Christopher Blyth ◽  
Heather Gidding ◽  
Tom Snelling ◽  
Parveen Fathima ◽  
...  
Keyword(s):  
Influenza Vaccine ◽  
Seasonal Influenza ◽  
Vaccine Coverage ◽  
Population Based ◽  
Vaccine Uptake ◽  
Respiratory Pathogens ◽  
Seasonal Influenza Vaccine ◽  
Specific Effects ◽  
Syncytial Virus ◽  
The Impact

Abstract Background Seasonal influenza vaccine is effective against influenza hospitalisations, but little is known about non-specific effects on other respiratory pathogens with similar seasonal patterns. We aimed to assess the causal impact of seasonal influenza vaccine on laboratory-confirmed hospitalisations for respiratory syncytial virus (RSV) in children using an instrumental variable (IV) strategy. Methods We used population-based probabilistically linked data on births, childhood immunisations, deaths, hospitalisations, perinatal and statewide microbiology data (2000-2013) in Western Australia (WA). Our analysis cohort included children up to age 7 years. We exploited WA’s unique preschool influenza vaccination policy commencing in 2008 and used this as an instrument for vaccination status. We estimated a system of two simultaneous probit equations: determinants of influenza vaccine uptake, and determinants of RSV-confirmed hospitalisation. Results Influenza vaccine coverage was low prior to 2008 but increased to 33.7% in children aged 6-23 months in 2009. RSV-hospitalisations ranged from 3.5/1000 children (12-23 months) to 6.4/1000 (6-12 months). Receipt of seasonal influenza vaccine reduced RSV-hospitalisations in the population cohort of children aged &lt;2 years by an average of 0.21% in the same year (p &lt; 0.001). Conclusions To our knowledge, this is the first analysis utilising an IV estimation strategy to assess the impact of influenza vaccine on RSV-hospitalisations. We estimated a small, but highly statistically significant impact that warrants further investigation using contemporary data. Key messages RSV is a leading cause of childhood morbidity. The role of influenza vaccine offering cross protection to RSV could be further explored prior to RSV vaccines being commercially available.

scholarly journals Spotlight influenza: The 2019/20 influenza season and the impact of COVID-19 on influenza surveillance in the WHO European Region

2021 ◽  
Vol 26 (40) ◽  
Author(s):  
Cornelia Adlhoch ◽  
Miriam Sneiderman ◽  
Oksana Martinuka ◽  
Angeliki Melidou ◽  
Nick Bundle ◽  
...  
Keyword(s):  
Influenza A ◽  
Influenza Season ◽  
Healthcare Access ◽  
World Health ◽  
European Region ◽  
Influenza Surveillance ◽  
Influenza B ◽  
Rapid Reduction ◽  
Influenza Activity ◽  
The Impact

Background Annual seasonal influenza activity in the northern hemisphere causes a high burden of disease during the winter months, peaking in the first weeks of the year. Aim We describe the 2019/20 influenza season and the impact of the COVID-19 pandemic on sentinel surveillance in the World Health Organization (WHO) European Region. Methods We analysed weekly epidemiological and virological influenza data from sentinel primary care and hospital sources reported by countries, territories and areas (hereafter countries) in the European Region. Results We observed co-circulation of influenza B/Victoria-lineage, A(H1)pdm09 and A(H3) viruses during the 2019/20 season, with different dominance patterns observed across the Region. A higher proportion of patients with influenza A virus infection than type B were observed. The influenza activity started in week 47/2019, and influenza positivity rate was ≥ 50% for 2 weeks (05–06/2020) rather than 5–8 weeks in the previous five seasons. In many countries a rapid reduction in sentinel reports and the highest influenza activity was observed in weeks 09–13/2020. Reporting was reduced from week 14/2020 across the Region coincident with the onset of widespread circulation of SARS-CoV-2. Conclusions Overall, influenza type A viruses dominated; however, there were varying patterns across the Region, with dominance of B/Victoria-lineage viruses in a few countries. The COVID-19 pandemic contributed to an earlier end of the influenza season and reduced influenza virus circulation probably owing to restricted healthcare access and public health measures.

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