scholarly journals The effect of COVID certificates on vaccine uptake, public health, and the economy

Author(s):  
Miquel Oliu-Barton ◽  
Bary SR Pradel ◽  
Nicolas Woloszko ◽  
Lionel Guetta-Jeanrenaud ◽  
Philippe Aghion ◽  
...  

Abstract In the COVID-19 pandemic, governments have used various interventions,1,2 including COVID certificates as proof of vaccination, recovery, or a recent negative test, required for individuals to access shops, restaurants, and education or workplaces.3 While arguments for and against COVID certificates have focused on reducing transmission and ethical concerns,4,5 the effect of the certificates on vaccine uptake, public health, and the economy requires investigation. We construct counterfactuals based on innovation diffusion theory6 and validate them with econometric methods7 to evaluate the impact of incentives created by COVID certificates in France, Germany, and Italy. We estimate that from their announcement during summer 2021 to the end of the year, the intervention led to increased vaccine uptake in France of 13.0 (95% CI 9.7–14.9) percentage points (p.p.) of the total population, in Germany 6.2 (2.6–6.9) p.p., and in Italy 9.7 (5.4–12.3) p.p.; averted an additional 3,979 (3,453–4,298) deaths in France (i.e., 31.7%), 1,133 (-312–1,358) in Germany (5.6%), and 1,331 (502–1,794) in Italy (14.0%); and prevented gross domestic product (GDP) losses of €6.0 (5.9–6.1) billion in France, €1.4 (1.3–1.5) billion in Germany, and €2.1 (2.0–2.2) billion in Italy. Notably, the application of COVID certificates substantially reduced the pressure on intensive care units (ICUs) and, in France, averted surpassing the occupancy levels where prior lockdowns were instated. Overall, our findings are more substantial than predicted8 and may help to inform decisions about when and how to employ COVID certificates to increase vaccination and thus avoid stringent interventions, such as closures, curfews, and lockdowns, with large social and economic consequences.

2020 ◽  
Vol 23 (3) ◽  
pp. 323-344 ◽  
Author(s):  
Sang-Wook (Stanley) Cho

Summary This paper estimates the effect of nonpharmaceutical intervention policies on public health during the COVID-19 outbreak by considering a counterfactual case for Sweden. Using a synthetic control approach, I find that strict initial lockdown measures play an important role in limiting the spread of the COVID-19 infection, as the infection cases in Sweden would have been reduced by almost 75 percent had its policymakers followed stricter containment policies. As people dynamically adjust their behaviour in response to information and policies, the impact of nonpharmaceutical interventions becomes visible, with a time lag of around 5 weeks. Supplementary robustness checks and an alternative difference-in-differences framework analysis do not fundamentally alter the main conclusions. Finally, extending the analysis to excess mortality, I find that the lockdown measures would have been associated with a lower excess mortality rate in Sweden by 25 percentage points, with a steep age gradient of 29 percentage points for the most vulnerable elderly cohort. The outcome of this study can assist policymakers in laying out future guidelines to further protect public health, as well as facilitate plans for economic recovery.


2020 ◽  
Vol 28 (1) ◽  
Author(s):  
Iben Axén ◽  
Cecilia Bergström ◽  
Marc Bronson ◽  
Pierre Côté ◽  
Casper Glissmann Nim ◽  
...  

Abstract Background In March 2020, the World Health Organization elevated the coronavirus disease (COVID-19) epidemic to a pandemic and called for urgent and aggressive action worldwide. Public health experts have communicated clear and emphatic strategies to prevent the spread of COVID-19. Hygiene rules and social distancing practices have been implemented by entire populations, including ‘stay-at-home’ orders in many countries. The long-term health and economic consequences of the COVID-19 pandemic are not yet known. Main text During this time of crisis, some chiropractors made claims on social media that chiropractic treatment can prevent or impact COVID-19. The rationale for these claims is that spinal manipulation can impact the nervous system and thus improve immunity. These beliefs often stem from nineteenth-century chiropractic concepts. We are aware of no clinically relevant scientific evidence to support such statements. We explored the internet and social media to collect examples of misinformation from Europe, North America, Australia and New Zealand regarding the impact of chiropractic treatment on immune function. We discuss the potential harm resulting from these claims and explore the role of chiropractors, teaching institutions, accrediting agencies, and legislative bodies. Conclusions Members of the chiropractic profession share a collective responsibility to act in the best interests of patients and public health. We hope that all chiropractic stakeholders will view the COVID-19 pandemic as a call to action to eliminate the unethical and potentially dangerous claims made by chiropractors who practise outside the boundaries of scientific evidence.


2018 ◽  
Vol 36 (3) ◽  
pp. 297-324
Author(s):  
Bruno Buonomo ◽  
Rossella Della Marca ◽  
Alberto d’Onofrio

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.


2020 ◽  
Author(s):  
Ian Njeru ◽  
David Kareko ◽  
Ngina Kisangau ◽  
Daniel Langat ◽  
Nzisa Liku ◽  
...  

Abstract Background: Infectious diseases remain one of the greatest threats to public health globally. Effective public health surveillance systems are therefore needed to provide timely and accurate information for early detection and response. In 2016, Kenya transitioned its surveillance system from a standalone web-based surveillance system to the more sustainable and integrated District Health Information System 2 (DHIS2). As part of Global Health Security Agenda (GHSA) initiatives in Kenya, training on use of the new system was conducted among surveillance officers. We evaluated the surveillance indicators during the transition period in order to assess the impact of this training on surveillance metrics and identify challenges affecting reporting rates. Methods: From February to May 2017, we analysed surveillance data for 13 intervention and 13 comparison counties. An intervention county was defined as one that had received refresher training on DHIS2 while a comparison county was one that had not received training. We evaluated the impact of the training by analysing completeness and timeliness of reporting 15 weeks before and 12 weeks after the training. A chi-square test of independence was used to compare the reporting rates between the two groups. A structured questionnaire was administered to the training participants to assess the challenges affecting surveillance reporting. Results: The completeness of reporting increased significantly after the training by 17 percentage points (from 45% to 62%) for the intervention group compared to 3 percentage points (49% to 52%) for the comparison group. Timeliness of reporting increased significantly by 21 percentage points (from 30% to 51%) for the intervention group compared to 7 percentage points (from 31% to 38%) for the comparison group. Major challenges identified for the low reporting rates included lack of budget support from government, lack of airtime for reporting, health workers strike, health facilities not sending surveillance data, use of wrong denominator to calculate reporting rates and surveillance officers being given other competing tasks. Conclusions: Training plays an important role in improving public health surveillance reporting. However, to improve surveillance reporting rates to the desired national targets, other challenges affecting reporting must be identified and addressed accordingly.


2020 ◽  
Vol 10 (11) ◽  
pp. 3880 ◽  
Author(s):  
Vasilis Papastefanopoulos ◽  
Pantelis Linardatos ◽  
Sotiris Kotsiantis

The ongoing COVID-19 pandemic has caused worldwide socioeconomic unrest, forcing governments to introduce extreme measures to reduce its spread. Being able to accurately forecast when the outbreak will hit its peak would significantly diminish the impact of the disease, as it would allow governments to alter their policy accordingly and plan ahead for the preventive steps needed such as public health messaging, raising awareness of citizens and increasing the capacity of the health system. This study investigated the accuracy of a variety of time series modeling approaches for coronavirus outbreak detection in ten different countries with the highest number of confirmed cases as of 4 May 2020. For each of these countries, six different time series approaches were developed and compared using two publicly available datasets regarding the progression of the virus in each country and the population of each country, respectively. The results demonstrate that, given data produced using actual testing for a small portion of the population, machine learning time series methods can learn and scale to accurately estimate the percentage of the total population that will become affected in the future.


2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
A Odone ◽  
V Gianfredi ◽  
B Frascella ◽  
F Balzarini ◽  
A Oradini Alacreu ◽  
...  

Abstract The second and final phase of the EUVIS (EUrope Vaccines ICT Strategies) project, coordinated by the School of Public Health of the University Vita-Salute San Raffaele in Milan (Italy), aims at collecting best practices on the use and impact of Information and Communication Technologies (ICT) and digital tools to increase vaccine uptake and ultimately vaccination coverage in Europe. The field of ICT has flourished in recent years revolutionizing the processes of gathering, spreading and utilizing health information among healthcare providers, citizens and mass media. In particular, we are interested in any digital technology that can improve vaccine uptake supporting actions aimed at both increasing the demand of vaccines (i.e provide access to information through telecommunications, networks, the Internet, wireless, mobile devices), and the supply of effective and efficient life-course immunization services (i.e ICT-based interventions to support immunization programmes delivery and their monitoring). Within EUVIS we have previously conducted a series of systematic reviews to pool available evidence from experimental studies on the impact of selected ICT-based intervention (i.e. e-mail reminders, personal health records, among others) to improve vaccine uptake and other associated outcomes. In the current study, second and final phase of the EUVIS project, we are conducting a survey at the European level to gather original data on the use and impact of ICT and digital tools within immunization programmes in selected countries. The survey tool was developed on the basis of findings from EUVIS phase one and experts' consultation; it consisted on a 55-item questionnaire, distributed to public health professionals working in health agencies, institutions and the academia to build “ICT and immunization” countries' profile, as well as to gather, pool and critically appraise data on perceived potential and challenges of immunization programmes' digitalization in Europe.


Author(s):  
Nereyda L. Sevilla

This research explored the role of air travel in the spread of infectious diseases, specifically severe acute respiratory syndrome (SARS), H1N1, Ebola, and pneumonic plague. Air travel provides the means for such diseases to spread internationally at extraordinary rates because infected passengers jump from coast to coast and continent to continent within hours. Outbreaks of diseases that spread from person to person test the effectiveness of current public health responses. This research used a mixed methods approach, including use of the Spatiotemporal Epidemiological Modeler, to model the spread of diseases, evaluate the impact of air travel on disease spread, and analyze the effectiveness of different public health strategies and travel policies. Modeling showed that the spread of Ebola and pneumonic plague is minimal and should not be a major air travel concern if an individual becomes infected. H1N1 and SARS have higher infection rates and air travel will facilitate the spread of disease nationally and internationally. To contain the spread of infectious diseases, aviation and public health authorities should establish tailored preventive measures at airports, capture contact information for ticketed passengers, expand the definition of “close contact,” and conduct widespread educational programs. The measures will put in place a foundation for containing the spread of infectious diseases via air travel and minimize the panic and economic consequences that may occur during an outbreak.


2020 ◽  
Vol 4 (3) ◽  
pp. 7-44 ◽  
Author(s):  
ANDRZEJ JARYNOWSKI ◽  
MONIKA WÓJTA-KEMPA ◽  
DANIEL PŁATEK ◽  
KAROLINA CZOPEK

Recently, the whole of Europe, including Poland, have been significantly affected by COVID-19 and its social and economic consequences which are already causing dozens of billions of euros monthly losses in Poland alone. Social behaviour has a fundamental impact on the dynamics of the spread of infectious diseases such as SARS-CoV-2, challenging the existing health infrastructure and social organization. Modelling and understanding mechanisms of social behaviour (e.g. panic and social distancing) and its contextualization with regard to Poland can contribute to better response to the outbreak on a national and local level. In the presented study we aim to investigate the impact of the COVID-19 on society by: (i) measuring the relevant activity in internet news and social media; (ii) analysing attitudes and demographic patterns in Poland. In the end, we are going to implement computational social science and digital epidemiology research approach to provide urgently needed information on social dynamics during the outbreak. This study is an ad hoc reaction only, and our goal is to signal the main areas of possible research to be done in the future and cover issues with direct or indirect relation to public health.


2020 ◽  
Author(s):  
Ian Njeru ◽  
David Kareko ◽  
Ngina Kisangau ◽  
Daniel Langat ◽  
Nzisa Liku ◽  
...  

Abstract Background: Effective public health surveillance systems are crucial for early detection and response to outbreaks. In 2016, Kenya transitioned its surveillance system from a standalone web-based surveillance system to the more sustainable and integrated District Health Information System 2 (DHIS2). As part of Global Health Security Agenda (GHSA) initiatives in Kenya, training on use of the new system was conducted among surveillance officers. We evaluated the surveillance indicators during the transition period in order to assess the impact of this training on surveillance metrics and identify challenges affecting reporting rates. Methods: From February to May 2017, we analysed surveillance data for 13 intervention and 13 comparison counties. An intervention county was defined as one that had received refresher training on DHIS2 while a comparison county was one that had not received training. We evaluated the impact of the training by analysing completeness and timeliness of reporting 15 weeks before and 12 weeks after the training. A chi-square test of independence was used to compare the reporting rates between the two groups. A structured questionnaire was administered to the training participants to assess the challenges affecting surveillance reporting. Results: The average completeness of reporting for the intervention counties increased from 45% to 62%, i.e. by 17 percentage points (95% CI 16.14 -17.86) compared to an increase from 49% to 52% for the comparison group, i.e. by 3 percentage points (95% CI 2.23 -3.77). The timeliness of reporting increased from 30% to 51%, i.e. by 21 percentage points (95% CI 20.16 - 21.84) for the intervention group, compared to an increase from 31% to 38% for the comparison group, i.e.by 7 percentage points (95% CI 6.27-7.73). Major challenges for the low reporting rates included lack of budget support from government, lack of airtime for reporting, health workers strike, health facilities not sending surveillance data, use of wrong denominator to calculate reporting rates and surveillance officers having other competing tasks. Conclusions: Training plays an important role in improving public health surveillance reporting. However, to improve surveillance reporting rates to the desired national targets, other challenges affecting reporting must be identified and addressed accordingly.


2022 ◽  
Vol 9 ◽  
Author(s):  
Henrique Lopes ◽  
Ricardo Baptista-Leite ◽  
Diogo Franco ◽  
Miguel A. Serra ◽  
Amparo Escudero ◽  
...  

Background: The WHO has defined international targets toward the elimination of hepatitis C by 2030. Most countries cannot be on track to achieve this goal unless many challenges are surpassed. The Let's End HepC (LEHC) tool aims to contribute to the control of hepatitis C. The innovation of this tool combines the modelling of public health policies (PHP) focused on hepatitis C with epidemiological modelling of the disease, obtaining a unique result that allows to forecast the impact of policy outcomes. The model was applied to several countries, including Spain.Methods: To address the stated objective, we applied the “Adaptive Conjoint Analysis” for PHP decision-making and Markov Chains in the LEHC modelling tool. The tool also aims to be used as an element of health literacy for patient advocacy through gamification mechanisms and country comparability. The LEHC project has been conducted in several countries, including Spain. The population segments comprised in the project are: People Who Inject Drugs (PWID), prisoners, blood products, remnant population.Results: A total of 24 PHP related to hepatitis C were included in the LEHC project. It was identified that Spain had fully implemented 14 of those policies to control hepatitis C. According to LEHC's model forecast, the WHO's Hepatitis C elimination goal on reducing the number of patients living with Hepatitis C to 10% can be achieved in Spain by 2026 if current policies are maintained. The model estimates that the total population in Spain, by 2026, is expected to comprise 26,367 individuals living with hepatitis C. Moreover, if the 24 PHP considered for this study are fully implemented in Spain, the elimination goal may be achieved in 2024, with 29,615 individuals living with hepatitis C by that year.Conclusion: The findings corroborate the view that Spain has set great efforts in directing PHP toward Hepatitis C Virus (HCV) elimination by 2030. However, there is still room for improvement, namely in further implementing 10 of the 24 PHP considered for the LEHC project. By maintaining the 14 PHP in force, the LEHC model estimates the HCV elimination in the country by 2026, and by 2024 if further measures are employed to control the disease.


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