scholarly journals The impact of vaccination on the evolution of COVID-19 in Portugal

2021 ◽  
Vol 19 (1) ◽  
pp. 936-952
Author(s):  
Beatriz Machado ◽  
◽  
Liliana Antunes ◽  
Constantino Caetano ◽  
João F. Pereira ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Symptom Onset ◽  
Vaccine Coverage ◽  
Disease Incidence ◽  
Transmission Intensity ◽  
Pharmacological Intervention ◽  
Type Model ◽  
Feedback Function ◽  
Health Authorities ◽  
The Impact

<abstract><p>In this work we use simple mathematical models to study the impact of vaccination against COVID-19 in Portugal. First, we fit a SEIR type model without vaccination to the Portuguese data on confirmed cases of COVID-19 by the date of symptom onset, from the beginning of the epidemic until the 23rd January of 2021, to estimate changes in the transmission intensity. Then, by including vaccination in the model we develop different scenarios for the fade-out of the non pharmacological intervention (NPIs) as vaccine coverage increases in the population according to Portuguese vaccination goals. We include a feedback function to mimic the implementation and relaxation of NPIs, according to some disease incidence thresholds defined by the Portuguese health authorities.</p></abstract>

scholarly journals The importance of sustained compliance with physical distancing during COVID-19 vaccination rollout

2021 ◽  
Author(s):  
Alexandra Teslya ◽  
Ganna Rozhnova ◽  
Thi Mui Pham ◽  
Daphne van Wees ◽  
Hendrik Nunner ◽  
...  
Keyword(s):  
Vaccination Coverage ◽  
Vaccine Coverage ◽  
Transmission Model ◽  
Cumulative Number ◽  
Vaccination Rates ◽  
Contact Rates ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Vaccination Campaigns ◽  
The Impact

Abstract Mass vaccination campaigns against SARS-CoV-2 are under way in many countries with the hope that increasing vaccination coverage will enable reducing current physical distancing measures. Compliance with these measures is waning, while more transmissible virus variants such as B.1.1.7 have emerged. Using SARS-CoV-2 transmission model we investigated the impact of the feedback between compliance, the incidence of infection, and vaccination coverage on the success of a vaccination programme in the population where waning of compliance depends on vaccine coverage. Our results suggest that the combination of fast waning compliance, slow vaccination rates, and more transmissible variants may result in a higher cumulative number of infections than in a situation without vaccination. These adverse effects can be alleviated if vaccinated individuals do not revert to pre-pandemic contact rates, and if non-vaccinated individuals remain compliant with physical distancing measures. Both require convincing, clear and appropriately targeted communication strategies by public health authorities.

scholarly journals When time-dependence in disease outcome risk is not captured by impact evaluation modeling studies: a measles vaccination case study

2021 ◽  
Author(s):  
Allison Portnoy ◽  
Yuli Lily Hsieh ◽  
Kaja Abbas ◽  
Petra Klepac ◽  
Heather Santos ◽  
...  
Keyword(s):  
Vaccine Coverage ◽  
Disease Incidence ◽  
Estimation Methods ◽  
Model Parameters ◽  
Time Varying ◽  
Modeling Studies ◽  
Measles Vaccination ◽  
Secondary Outcomes ◽  
The Impact

Background: In modeling studies that evaluate the effects of health programs, the risk of secondary outcomes attributable to infection can vary with underlying disease incidence. Consequently, the impact of interventions on secondary outcomes would not be proportional to incidence reduction. Here we use a case study on measles vaccine program to demonstrate how failure to capture this non-linear relationship can lead to over- or under-estimation. Methods: We used a published model of measles CFR that depends on incidence and vaccine coverage to illustrate the effects of: (1) assuming higher CFR in 'no-vaccination' scenarios; (2) time-varying CFRs over the past; and (3) time-varying CFRs in future projections on measles impact estimation. We evaluated how different assumptions on vaccine coverage, measles incidence, and CFR levels in 'no-vaccination' scenarios affect estimation of future deaths averted by measles vaccination. Results: Compared to constant CFRs, aligning both 'vaccination' and 'no-vaccination' scenarios with time variant measles CFR estimates led to larger differences in mortality in historical years and lower in future years. Conclusions: To assess consequences of interventions, impact estimates should consider the effect of 'no-intervention' scenario assumptions on model parameters to project estimated impact for alternative scenarios according to intervention strategies and investment decisions.

Mapping global variation in dengue transmission intensity

2020 ◽  
Vol 12 (528) ◽  
pp. eaax4144 ◽  
Author(s):  
Lorenzo Cattarino ◽  
Isabel Rodriguez-Barraquer ◽  
Natsuko Imai ◽  
Derek A. T. Cummings ◽  
Neil M. Ferguson
Keyword(s):  
Disease Incidence ◽  
The Philippines ◽  
Transmission Intensity ◽  
Global Public Health ◽  
African Countries ◽  
Cross Sectional ◽  
Force Of Infection ◽  
High Transmission ◽  
Dengue Transmission ◽  
The Impact

Intervention planning for dengue requires reliable estimates of dengue transmission intensity. However, current maps of dengue risk provide estimates of disease burden or the boundaries of endemicity rather than transmission intensity. We therefore developed a global high-resolution map of dengue transmission intensity by fitting environmentally driven geospatial models to geolocated force of infection estimates derived from cross-sectional serological surveys and routine case surveillance data. We assessed the impact of interventions on dengue transmission and disease using Wolbachia-infected mosquitoes and the Sanofi-Pasteur vaccine as specific examples. We predicted high transmission intensity in all continents straddling the tropics, with hot spots in South America (Colombia, Venezuela, and Brazil), Africa (western and central African countries), and Southeast Asia (Thailand, Indonesia, and the Philippines). We estimated that 105 [95% confidence interval (CI), 95 to 114] million dengue infections occur each year with 51 (95% CI, 32 to 66) million febrile disease cases. Our analysis suggests that transmission-blocking interventions such as Wolbachia, even at intermediate efficacy (50% transmission reduction), might reduce global annual disease incidence by up to 90%. The Sanofi-Pasteur vaccine, targeting only seropositive recipients, might reduce global annual disease incidence by 20 to 30%, with the greatest impact in high-transmission settings. The transmission intensity map presented here, and made available for download, may help further assessment of the impact of dengue control interventions and prioritization of global public health efforts.

scholarly journals The importance of sustained compliance with physical distancing during COVID-19 vaccination rollout

2021 ◽  
Author(s):  
Alexandra Teslya ◽  
Ganna Rozhnova ◽  
Thi Mui Pham ◽  
Daphne van Wees ◽  
Hendrik Nunner ◽  
...  
Keyword(s):  
Vaccination Coverage ◽  
Vaccine Coverage ◽  
Transmission Model ◽  
Cumulative Number ◽  
Vaccination Rates ◽  
Contact Rates ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Vaccination Campaigns ◽  
The Impact

Abstract Mass vaccination campaigns against SARS-CoV-2 are under way in many countries with the hope that increasing vaccination coverage will enable reducing current physical distancing measures. Compliance with these measures is waning, while more transmissible virus variants such as B.1.1.7 have emerged. Using SARS-CoV-2 transmission model we investigated the impact of the feedback between compliance, the incidence of infection, and vaccination coverage on the success of a vaccination programme in the population where waning of compliance depends on vaccine coverage. Our results suggest that the combination of fast waning compliance, slow vaccination rates, and more transmissible variants may result in a higher cumulative number of infections than in a situation without vaccination. These adverse effects can be alleviated if vaccinated individuals do not revert to pre-pandemic contact rates, and if non-vaccinated individuals remain compliant with physical distancing measures. Both require convincing, clear and appropriately targeted communication strategies by public health authorities.

scholarly journals Predicting Required COVID-19 Vaccine Coverage and its Impact in Sierra Leone Using Mathematical models

2021 ◽  
Author(s):  
Abdul A. Kamara ◽  
Joseph A. L. Kamara ◽  
Sallieu K. Samura
Keyword(s):  
Mathematical Models ◽  
Explicit Formula ◽  
Sierra Leone ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Vaccine Coverage ◽  
Transmission Rate ◽  
Asymptomatic Infection ◽  
The Impact ◽  
The Basic Reproduction Number

Abstract In this article, we predict the required vaccine coverage to eradicate the COVID-19 outbreak in Sierra Leone. We also, investigate the impact of facemask and vaccine coverage on the spread of the COVID-19 virus using a modified symptomatic-asymptomatic infection transmissions Susceptible-Latent-Infectious-Asymptomatic-Recovered (SLIAR) model. We derived an explicit formula for the basic reproduction number and used it to understand the dynamics of the disease when it is greater than unity. Numerically, we show that 58 per cent of the Sierra Leone national population required vaccination to eradicate the COVID-19 virus. Also, the SLIAR with vaccine model results reveal that the impact of using facemask is very challenging to understand and the vaccine coverage decrease the infected transmission rate but cannot completely eradicate the infection.

COVID-19: Time-Dependent Effective Reproduction Number and Sub-notification Effect Estimation Modeling (Preprint)

2020 ◽  
Author(s):  
Eduardo Atem De Carvalho ◽  
Rogerio Atem De Carvalho
Keyword(s):  
New York ◽  
Reproduction Number ◽  
Moving Average ◽  
Real Data ◽  
Time Dependent ◽  
Initial Value ◽  
Health Authorities ◽  
Reproduction Numbers ◽  
Effect Estimation ◽  
The Impact

BACKGROUND Since the beginning of the COVID-19 pandemic, researchers and health authorities have sought to identify the different parameters that govern their infection and death cycles, in order to be able to make better decisions. In particular, a series of reproduction number estimation models have been presented, with different practical results. OBJECTIVE This article aims to present an effective and efficient model for estimating the Reproduction Number and to discuss the impacts of sub-notification on these calculations. METHODS The concept of Moving Average Method with Initial value (MAMI) is used, as well as a model for Rt, the Reproduction Number, is derived from experimental data. The models are applied to real data and their performance is presented. RESULTS Analyses on Rt and sub-notification effects for Germany, Italy, Sweden, United Kingdom, South Korea, and the State of New York are presented to show the performance of the methods here introduced. CONCLUSIONS We show that, with relatively simple mathematical tools, it is possible to obtain reliable values for time-dependent, incubation period-independent Reproduction Numbers (Rt). We also demonstrate that the impact of sub-notification is relatively low, after the initial phase of the epidemic cycle has passed.

scholarly journals Modelling the impact of delaying vaccination against SARS-CoV-2 assuming unlimited vaccine supply

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Marcos Amaku ◽  
Dimas Tadeu Covas ◽  
Francisco Antonio Bezerra Coutinho ◽  
Raymundo Soares Azevedo ◽  
Eduardo Massad
Keyword(s):  
Mathematical Model ◽  
Vaccination Campaign ◽  
Vaccination Rate ◽  
Sao Paulo ◽  
The State ◽  
São Paulo ◽  
Health Authorities ◽  
The World ◽  
The Moment ◽  
The Impact

Abstract Background At the moment we have more than 177 million cases and 3.8 million deaths (as of June 2021) around the world and vaccination represents the only hope to control the pandemic. Imperfections in planning vaccine acquisition and difficulties in implementing distribution among the population, however, have hampered the control of the virus so far. Methods We propose a new mathematical model to estimate the impact of vaccination delay against the 2019 coronavirus disease (COVID-19) on the number of cases and deaths due to the disease in Brazil. We apply the model to Brazil as a whole and to the State of Sao Paulo, the most affected by COVID-19 in Brazil. We simulated the model for the populations of the State of Sao Paulo and Brazil as a whole, varying the scenarios related to vaccine efficacy and compliance from the populations. Results The model projects that, in the absence of vaccination, almost 170 thousand deaths and more than 350 thousand deaths will occur by the end of 2021 for Sao Paulo and Brazil, respectively. If in contrast, Sao Paulo and Brazil had enough vaccine supply and so started a vaccination campaign in January with the maximum vaccination rate, compliance and efficacy, they could have averted more than 112 thousand deaths and 127 thousand deaths, respectively. In addition, for each month of delay the number of deaths increases monotonically in a logarithmic fashion, for both the State of Sao Paulo and Brazil as a whole. Conclusions Our model shows that the current delay in the vaccination schedules that is observed in many countries has serious consequences in terms of mortality by the disease and should serve as an alert to health authorities to speed the process up such that the highest number of people to be immunized is reached in the shortest period of time.

scholarly journals 545. The Impact of COVID-19 on African Americans’ Health Attitudes and Information Seeking Behavior

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S338-S339
Author(s):  
Katherine Kricorian ◽  
Ozlem Equils ◽  
Karin Kricorian ◽  
Brianna Rochebrun
Keyword(s):  
African Americans ◽  
Information Seeking ◽  
Disease Incidence ◽  
Family Members ◽  
National Sample ◽  
Health Attitudes ◽  
Health News ◽  
Before And After ◽  
Science And Government ◽  
The Impact

Abstract Background African-Americans suffer a disproportionate impact from COVID-19, comprising about 24% of deaths while representing 13% of the US population. We conducted a study to understand COVID-19’s impact on African-Americans’ health attitudes. Methods In April 2020, we surveyed online a national sample of US adults on their health attitudes and behaviors before and after the COVID-19 outbreak. Comparisons were analyzed using chi-squared tests. Results A total of 2,544 individuals completed the survey: 473 African-Americans, 282 Hispanics and 1,799 Caucasians responded. The mean ages of each group were 41.4 ± 11 years, 38.0 ± 11 years and 45.7 ± 13 years, respectively. Before COVID-19, African-Americans were least likely to report they had trust in science (53% vs. 68% for Hispanics and 77% for Caucasians; p&lt; .01) and government (16% vs. 27% and 28%; p&lt; .01). After COVID-19, the percentage of African-Americans who had trust in science and government fell further to 44% (p&lt; .01) and 9% (p&lt; .01), respectively, and remained significantly lower than the other two groups. Twice as many African-Americans vs. Caucasians stopped following science and health news after COVID-19 (9% vs. 4%, p&lt; .01). The percentage of African-Americans who reported anxiety about their health rose from 30% pre-COVID to 53% after the outbreak (p&lt; .01), and the percentage who reported anxiety about their family members’ health rose from 35% to 61% (p&lt; .01). Only 25% of African-Americans surveyed agreed that if they contracted COVID-19, they were confident they would get the healthcare needed. Conclusion After COVID-19, African-Americans’ trust in science and government fell and a meaningful percentage stopped following science and health news, possibly reducing access to important health information. The percentage of African-Americans reporting anxiety about the future, about their health and about their family members’ health all increased significantly after COVID-19. Only a minority of African-Americans agreed they would get the needed healthcare if they contracted COVID-19. These findings have implications for the mental health and behavioral impacts of COVID-19 on African-Americans and for the development of health communications to high-disease-incidence populations. Disclosures All Authors: No reported disclosures

scholarly journals Impact of national influenza vaccination strategy in severe influenza outcomes among the high-risk Portuguese population

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Ausenda Machado ◽  
Irina Kislaya ◽  
Amparo Larrauri ◽  
Carlos Matias Dias ◽  
Baltazar Nunes
Keyword(s):  
High Risk ◽  
Influenza Vaccination ◽  
Seasonal Influenza ◽  
Vaccine Coverage ◽  
Vaccination Strategy ◽  
High Risk Population ◽  
Risk Population ◽  
Seasonal Influenza Vaccination ◽  
Severe Influenza ◽  
The Impact

Abstract Background All aged individuals with a chronic condition and those with 65 and more years are at increased risk of severe influenza post-infection complications. There is limited research on cases averted by the yearly vaccination programs in high-risk individuals. The objective was to estimate the impact of trivalent seasonal influenza vaccination on averted hospitalizations and death among the high-risk population in Portugal. Methods The impact of trivalent seasonal influenza vaccination was estimated using vaccine coverage, vaccine effectiveness and the number of influenza-related hospitalizations and deaths. The number of averted events (NAE), prevented fraction (PF) and number needed to vaccinate (NVN) were estimated for seasons 2014/15 to 2016/17. Results The vaccination strategy averted on average approximately 1833 hospitalizations and 383 deaths per season. Highest NAE was observed in the ≥65 years population (85% of hospitalizations and 95% deaths) and in the 2016/17 season (1957 hospitalizations and 439 deaths). On average, seasonal vaccination prevented 21% of hospitalizations in the population aged 65 and more, and 18.5% in the population with chronic conditions. The vaccination also prevented 29% and 19.5% of deaths in each group of the high-risk population. It would be needed to vaccinate 3360 high-risk individuals, to prevent one hospitalization and 60,471 high-risk individuals to prevent one death. Conclusion The yearly influenza vaccination campaigns had a sustained positive benefit for the high-risk population, reducing hospitalizations and deaths. These results can support public health plans toward increased vaccine coverage in high-risk groups.

scholarly journals Conceptualizing the effects of the COVID-19 pandemic on people with opioid use disorder: an application of the social ecological model

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Ethan Cowan ◽  
Maria R. Khan ◽  
Siri Shastry ◽  
E. Jennifer Edelman
Keyword(s):  
Structural Changes ◽  
Ecological Model ◽  
Disease Incidence ◽  
Opioid Use Disorder ◽  
Social Ecological Model ◽  
Physical And Mental Health ◽  
Opioid Use ◽  
Social Ecological ◽  
The Social ◽  
The Impact

AbstractThe COVID-19 pandemic has resulted in unparalleled societal disruption with wide ranging effects on individual liberties, the economy, and physical and mental health. While no social strata or population has been spared, the pandemic has posed unique and poorly characterized challenges for individuals with opioid use disorder (OUD). Given the pandemic’s broad effects, it is helpful to organize the risks posed to specific populations using theoretical models. These models can guide scientific inquiry, interventions, and public policy. Models also provide a visual image of the interplay of individual-, network-, community-, structural-, and pandemic-level factors that can lead to increased risks of infection and associated morbidity and mortality for individuals and populations. Such models are not unidirectional, in that actions of individuals, networks, communities and structural changes can also affect overall disease incidence and prevalence. In this commentary, we describe how the social ecological model (SEM) may be applied to describe the theoretical effects of the COVID-19 pandemic on individuals with opioid use disorder (OUD). This model can provide a necessary framework to systematically guide time-sensitive research and implementation of individual-, community-, and policy-level interventions to mitigate the impact of the COVID-19 pandemic on individuals with OUD.

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