scholarly journals Impact of public health interventions to curb SARS-CoV-2 spread assessed by an evidence-educated Delphi panel and tailored SEIR model

2021 ◽  
Author(s):  
Bernd Brüggenjürgen ◽  
Hans-Peter Stricker ◽  
Lilian Krist ◽  
Miriam Ortiz ◽  
Thomas Reinhold ◽  
...  
Keyword(s):  
Public Health ◽  
Transmission Rate ◽  
Latency Period ◽  
Policy Decision ◽  
Sensitivity Analyses ◽  
Delphi Panel ◽  
Time Step ◽  
Seir Model ◽  
Health Policy Decision ◽  
The Impact

Abstract Aim To use a Delphi-panel-based assessment of the effectiveness of different non-pharmaceutical interventions (NPI) in order to retrospectively approximate and to prospectively predict the SARS-CoV-2 pandemic progression via a SEIR model (susceptible, exposed, infectious, removed). Methods We applied an evidence-educated Delphi-panel approach to elicit the impact of NPIs on the SARS-CoV-2 transmission rate R0 in Germany. Effectiveness was defined as the product of efficacy and compliance. A discrete, deterministic SEIR model with time step of 1 day, a latency period of 1.8 days, duration of infectiousness of 5 days, and a share of the total population of 15% assumed to be protected by immunity was developed in order to estimate the impact of selected NPI measures on the course of the pandemic. The model was populated with the Delphi-panel results and varied in sensitivity analyses. Results Efficacy and compliance estimates for the three most effective NPIs were as follows: test and isolate 49% (efficacy)/78% (compliance), keeping distance 42%/74%, personal protection masks (cloth masks or other face masks) 33%/79%. Applying all NPI effectiveness estimates to the SEIR model resulted in a valid replication of reported occurrence of the German SARS-CoV-2 pandemic. A combination of four NPIs at consented compliance rates might curb the CoViD-19 pandemic. Conclusion Employing an evidence-educated Delphi-panel approach can support SARS-CoV-2 modelling. Future curbing scenarios require a combination of NPIs. A Delphi-panel-based NPI assessment and modelling might support public health policy decision making by informing sequence and number of needed public health measures.

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 A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wilfredo Angulo ◽  
José M. Ramírez ◽  
Dany De Cecchis ◽  
Juan Primera ◽  
Henry Pacheco ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Risk Perceptions ◽  
Transmission Rate ◽  
Early Stage ◽  
Individual Risk ◽  
Seir Model ◽  
Proposed Model ◽  
Probable Site ◽  
Adjusted Model ◽  
The Impact

AbstractCOVID-19 is a highly infectious disease that emerged in China at the end of 2019. The COVID-19 pandemic is the first known pandemic caused by a coronavirus, namely, the new and emerging SARS-CoV-2 coronavirus. In the present work, we present simulations of the initial outbreak of this new coronavirus using a modified transmission rate SEIR model that takes into account the impact of government actions and the perception of risk by individuals in reaction to the proportion of fatal cases. The parameters related to these effects were fitted to the number of infected cases in the 33 provinces of China. The data for Hubei Province, the probable site of origin of the current pandemic, were considered as a particular case for the simulation and showed that the theoretical model reproduces the behavior of the data, thus indicating the importance of combining government actions and individual risk perceptions when the proportion of fatal cases is greater than $$4\%$$ 4 % . The results show that the adjusted model reproduces the behavior of the data quite well for some provinces, suggesting that the spread of the disease differs when different actions are evaluated. The proposed model could help to predict outbreaks of viruses with a biological and molecular structure similar to that of SARS-CoV-2.

scholarly journals The impact of temperature and absolute humidity on the coronavirus disease 2019 (COVID-19) outbreak - evidence from China

2020 ◽  
Author(s):  
Peng Shi ◽  
Yinqiao Dong ◽  
Huanchang Yan ◽  
Xiaoyang Li ◽  
Chenkai Zhao ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Infectious Diseases ◽  
Transmission Rate ◽  
Mainland China ◽  
Weather Condition ◽  
Absolute Humidity ◽  
List Type ◽  
Seir Model ◽  
Provincial Level ◽  
The Impact

ABSTRACTOBJECTIVETo investigate the impact of temperature and absolute humidity on the coronavirus disease 2019 (COVID-19) outbreak.DESIGNEcological study.SETTING31 provincial-level regions in mainland China.MAIN OUTCOME MEASURESData on COVID-19 incidence and climate between Jan 20 and Feb 29, 2020.RESULTSThe number of new confirm COVID-19 cases in mainland China peaked on Feb 1, 2020. COVID-19 daily incidence were lowest at -10 °C and highest at 10 °C, while the maximum incidence was observed at the absolute humidity of approximately 7 g/m3. COVID-19 incidence changed with temperature as daily incidence decreased when the temperature rose. No significant association between COVID-19 incidence and absolute humidity was observed in distributed lag nonlinear models. Additionally, A modified susceptible-exposed-infectious-recovered (M-SEIR) model confirmed that transmission rate decreased with the increase of temperature, leading to further decrease of infection rate and outbreak scale.CONCLUSIONTemperature is an environmental driver of the COVID-19 outbreak in China. Lower and higher temperatures might be positive to decrease the COVID-19 incidence. M-SEIR models help to better evaluate environmental and social impacts on COVID-19.What is already known on this topicMany infectious diseases present an environmental pattern in their incidence.Environmental factors, such as climate and weather condition, could drive the space and time correlations of infectious diseases, including influenza.Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be transmitted through aerosols, large droplets, or direct contact with secretions (or fomites) as influenza virus can.Little is known about environmental pattern in COVID-19 incidence.What this study addsThe significant association between COVID-19 daily incidence and temperature was confirmed, using 3 methods, based on the data on COVID-19 and weather from 31 provincial-level regions in mainland China.Environmental factors were considered on the basis of SEIR model, and a modified susceptible-exposed-infectious-recovered (M-SEIR) model was developed.Simulations of the COVID-19 outbreak in Wuhan presented similar effects of temperature on incidence as the incidence decrease with the increase of temperature.

scholarly journals The Epidemiological and Economic Impact of a Cell-Based Quadrivalent Influenza Vaccine in Adults in the US: A Dynamic Modeling Approach

Vaccines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1095
Author(s):  
Van Hung Nguyen ◽  
Yvonne Hilsky ◽  
Joaquin Mould-Quevedo
Keyword(s):  
Public Health ◽  
Influenza Vaccine ◽  
Economic Impact ◽  
Influenza Vaccines ◽  
Sensitivity Analyses ◽  
Life Years ◽  
The Us ◽  
A Cell ◽  
The Impact ◽  
Quadrivalent Influenza Vaccine

Mutations of the H3N2 vaccine strain during the egg-based vaccine manufacturing process partly explain the suboptimal effectiveness of traditional seasonal influenza vaccines. Cell-based influenza vaccines improve antigenic match and vaccine effectiveness by avoiding such egg-adaptation. This study evaluated the public health and economic impact of a cell-based quadrivalent influenza vaccine (QIVc) in adults (18–64 years) compared to the standard egg-based quadrivalent influenza vaccine (QIVe) in the US. The impact of QIVc over QIVe in public health and cost outcomes was estimated using a dynamic age-structured SEIR transmission model, which accounted for four circulating influenza strains [A/H1N1pdm9, A/H3N2, B(Victoria), and B(Yamagata)] and was calibrated on the 2013–2018 influenza seasons. The robustness of the results was assessed in univariate and probabilistic sensitivity analyses. Switching from QIVe to QIVc in 18- to 64-year-olds may prevent 5.7 million symptomatic cases, 1.8 million outpatient visits, 50,000 hospitalizations, and 5453 deaths annually. The switch could save 128,000 Quality-Adjusted Life Years (QALYs) and US $ 845 M in direct costs, resulting in cost-savings in a three-year time horizon analysis. Probabilistic sensitivity analyses confirmed the robustness of the cost-saving result. The analysis shows that QIVc is expected to prevent hospitalizations and deaths, and result in substantial savings in healthcare costs.

scholarly journals Evolution of disease transmission rate during the course of SARS-COV-2: Patterns and determinants

2020 ◽  
Author(s):  
Jie Zhu ◽  
Blanca Gallego
Keyword(s):  
Public Health ◽  
Disease Transmission ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Region Of Interest ◽  
Health Interventions ◽  
Transmission Model ◽  
Public Health Interventions ◽  
Containment Measures ◽  
The Impact

Abstract To date, many studies have argued the potential impact of public health interventions on flattening the epidemic curve of SARS-CoV-2. Most of them have focused on simulating the impact of interventions in a region of interest by manipulating contact patterns and key transmission parameters to reflect different scenarios. Our study looks into the evolution of the daily effective reproduction number during the epidemic via a stochastic transmission model. We found this measure (although model-dependent) provides an early signal of the efficacy of containment measures. This epidemiological parameter when updated in real-time can also provide better predictions of future outbreaks. Our results found a substantial variation in the effect of public health interventions on the dynamic of SARS-CoV-2 transmission over time and across countries, that could not be explained solely by the timing and number of the adopted interventions. This suggests that further knowledge about the idiosyncrasy of their implementation and effectiveness is required. Although sustained containment measures have successfully lowered growth in disease transmission, more than half of the 101 studied countries failed to maintain the effective reproduction number close to or below 1. This resulted in continued growth in reported cases. Finally, we were able to predict with reasonable accuracy which countries would experience outbreaks in the next 30 days.

scholarly journals HIV testing by public health centers and municipalities, and new HIV cases during the COVID-19 pandemic in Japan

2020 ◽  
Author(s):  
Keisuke Ejima ◽  
Yoshiki Koizumi ◽  
Nao Yamamoto ◽  
Molly Rosenberg ◽  
Christina Ludema ◽  
...  
Keyword(s):  
Public Health ◽  
Hiv Testing ◽  
Health Centers ◽  
Added Value ◽  
Sensitivity Analyses ◽  
Related Data ◽  
Time Restrictions ◽  
Hiv Test ◽  
Aids Diagnosis ◽  
The Impact

AbstractBackgroundDuring the COVID-19 outbreak, medical resources were primarily allocated to COVID-19, which might have reduced facility capacity for HIV testing. Further, people may have opted against HIV testing during this period to avoid COVID-19 exposure. We investigate the influence of the COVID-19 pandemic on HIV testing and its consequences in Japan.MethodsWe analysed quarterly HIV/AIDS-related data from 2015 to the second quarter of 2020 using an anomaly detection approach. The data included the number of consultations that public health centers received, the number of HIV tests performed by public health centers or municipalities, and the number of newly reported HIV cases with and without AIDS diagnosis. As sensitivity analyses, we performed the same analysis for two subgroups: men who have sex with men (MSM) and non-Japanese.FindingsThe number of HIV tests (9,584 vs. 35,908 in the year-before period) and consultations (11,689 vs. 32,565) performed by public health centers significantly declined in the second quarter of 2020, while the proportion of HIV cases with AIDS diagnosis among all HIV cases (36·2% vs. 26·4%) significantly increased after removing the trend and seasonality effects. The number of HIV cases without AIDS diagnosis numerically decreased (166 vs. 217), although the reduction was not significant. We confirmed similar trend for the MSM and non-Japanese groups.InterpretationThe current HIV testing system including public health centers misses more HIV cases at the early phase of the infection during the pandemic. Given that the clear epidemiological picture of HIV incidence during the pandemic is still uncertain, continuously monitoring the situation as well as securing sufficient test resources using self-test is essential.FundingJapan Society for the Promotion of Science, Japan Science and Technology Agency, Japan Agency for Medical Research and Development.Research in contextEvidence before this studyBefore this study, we searched PubMed, Medline, and Google Scholar on Oct 12, 2020, for articles investigated the number of HIV test and HIV cases during the COVID-19 pandemic in Japan, using the search terms “novel coronavirus” or “SARS-CoV-2”, and “HIV” or “AIDS”, and “Japan”, with no time restrictions. We found no published work relevant to our study.Added value of this studyDuring the COVID-19 pandemic in Japan, the public health centers and municipalities temporarily suspended facility-based HIV testing to concentrate their limited resources to COVID-19 testing. We investigated the impact of the COVID-19 pandemic on the number of HIV tests in public health centers and municipalities, and on the number of HIV cases with and without AIDS diagnosis. We confirmed that the number of the test declined in the second quarter (April to June) of 2020, and the proportion of HIV with AIDS diagnosis among all HIV cases increased during the same period.Implications of all the available evidenceProviding sufficient HIV testing opportunities even during the pandemic, when facility-based testing is challenging, is necessary for better clinical and public health outcomes. Self-testing and home specimen collection (e.g. dried blood spot or oral fluid test) could be a key to fill the gap between the need for HIV testing and the constraints related to the COVID-19 outbreak.

scholarly journals Mathematical Parameters of the COVID-19 Epidemic in Brazil and Evaluation of the Impact of Different Public Health Measures

Biology ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 220 ◽  
Author(s):  
Renato M. Cotta ◽  
Carolina P. Naveira-Cotta ◽  
Pierre Magal
Keyword(s):  
Public Health ◽  
Initial Conditions ◽  
Transmission Rate ◽  
Time Variable ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Problem Model ◽  
Social Distancing ◽  
Health Measures ◽  
The Impact

A SIRU-type epidemic model is employed for the prediction of the COVID-19 epidemy evolution in Brazil, and analyze the influence of public health measures on simulating the control of this infectious disease. The proposed model allows for a time variable functional form of both the transmission rate and the fraction of asymptomatic infectious individuals that become reported symptomatic individuals, to reflect public health interventions, towards the epidemy control. An exponential analytical behavior for the accumulated reported cases evolution is assumed at the onset of the epidemy, for explicitly estimating initial conditions, while a Bayesian inference approach is adopted for the estimation of parameters by employing the direct problem model with the data from the first phase of the epidemy evolution, represented by the time series for the reported cases of infected individuals. The evolution of the COVID-19 epidemy in China is considered for validation purposes, by taking the first part of the dataset of accumulated reported infectious individuals to estimate the related parameters, and retaining the rest of the evolution data for direct comparison with the predicted results. Then, the available data on reported cases in Brazil from 15 February until 29 March, is used for estimating parameters and then predicting the first phase of the epidemy evolution from these initial conditions. The data for the reported cases in Brazil from 30 March until 23 April are reserved for validation of the model. Then, public health interventions are simulated, aimed at evaluating the effects on the disease spreading, by acting on both the transmission rate and the fraction of the total number of the symptomatic infectious individuals, considering time variable exponential behaviors for these two parameters. This first constructed model provides fairly accurate predictions up to day 65 below 5% relative deviation, when the data starts detaching from the theoretical curve. From the simulated public health intervention measures through five different scenarios, it was observed that a combination of careful control of the social distancing relaxation and improved sanitary habits, together with more intensive testing for isolation of symptomatic cases, is essential to achieve the overall control of the disease and avoid a second more strict social distancing intervention. Finally, the full dataset available by the completion of the present work is employed in redefining the model to yield updated epidemy evolution estimates.

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