scholarly journals Quantifying the impact of nonpharmaceutical interventions during the COVID-19 outbreak: The case of Sweden

2020 ◽  
Vol 23 (3) ◽  
pp. 323-344 ◽  
Author(s):  
Sang-Wook (Stanley) Cho
Keyword(s):  
Public Health ◽  
Excess Mortality ◽  
Time Lag ◽  
Synthetic Control ◽  
Framework Analysis ◽  
Control Approach ◽  
Percentage Points ◽  
Elderly Cohort ◽  
Nonpharmaceutical Interventions ◽  
The Impact

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.

A Control Approach to Guide Nonpharmaceutical Interventions in the Treatment of COVID-19 Disease Using a SEIHRD Dynamical Model

2021 ◽  
Vol 30 (3) ◽  
pp. 323-346
Author(s):  
Fernando Pazos ◽  
◽  
Flavia E. Felicioni ◽  
Keyword(s):  
Public Health ◽  
Ad Hoc ◽  
Early Stage ◽  
Control Law ◽  
Parametric Uncertainties ◽  
Social Unrest ◽  
Control Approach ◽  
Health Measures ◽  
Optimal Intensity ◽  
Nonpharmaceutical Interventions

The recent worldwide epidemic of COVID-19 disease, for which there are no medications to cure it and the vaccination is still at an early stage, led to the adoption of public health measures by governments and populations in most of the affected countries to avoid the contagion and its spread. These measures are known as nonpharmaceutical interventions (NPIs), and their implementation clearly produces social unrest as well as greatly affects the economy. Frequently, NPIs are implemented with an intensity quantified in an ad hoc manner. Control theory offers a worthwhile tool for determining the optimal intensity of the NPIs in order to avoid the collapse of the healthcare system while keeping them as low as possible, yielding concrete guidance to policymakers. A simple controller, which generates a control law that is easy to calculate and to implement is proposed. This controller is robust to large parametric uncertainties in the model used and to some level of noncompliance with the NPIs.

scholarly journals Using RE-AIM to examine the potential public health impact of an integrated collaborative care intervention for weight and depression management in primary care: Results from the RAINBOW trial

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248339
Author(s):  
Megan A. Lewis ◽  
Laura K. Wagner ◽  
Lisa G. Rosas ◽  
Nan Lv ◽  
Elizabeth M. Venditti ◽  
...  
Keyword(s):  
Public Health ◽  
Primary Care ◽  
Collaborative Care ◽  
Health Impact ◽  
Public Health Impact ◽  
Integrative Approach ◽  
Structured Interviews ◽  
Framework Analysis ◽  
Care Intervention ◽  
The Impact

Background An integrated collaborative care intervention was used to treat primary care patients with comorbid obesity and depression in a randomized clinical trial. To increase wider uptake and dissemination, information is needed on translational potential. Methods The trial collected longitudinal, qualitative data at baseline, 6 months (end of intensive treatment), 12 months (end of maintenance treatment), and 24 months (end of follow-up). Semi-structured interviews (n = 142) were conducted with 54 out of 409 randomly selected trial participants and 37 other stakeholders, such as recruitment staff, intervention staff, and clinicians. Using a Framework Analysis approach, we examined themes across time and stakeholder groups according to the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework. Results At baseline, participants and other stakeholders reported being skeptical of the collaborative care approach related to some RE-AIM dimensions. However, over time they indicated greater confidence regarding the potential for future public health impact. They also provided information on barriers and actionable information to enhance program reach, effectiveness, adoption, implementation, and maintenance. Conclusions RE-AIM provided a useful framework for understanding how to increase the impact of a collaborative and integrative approach for treating comorbid obesity and depression. It also demonstrates the utility of using the framework as a planning tool early in the evidence-generation pipeline.

scholarly journals Use of technology for public health surveillance reporting: opportunities, challenges and lessons learnt from Kenya

2020 ◽  
Author(s):  
Ian Njeru ◽  
David Kareko ◽  
Ngina Kisangau ◽  
Daniel Langat ◽  
Nzisa Liku ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Comparison Group ◽  
Intervention Group ◽  
Health Surveillance ◽  
Surveillance Data ◽  
Percentage Points ◽  
Reporting Rates ◽  
The Impact

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.

scholarly journals A control approach to the Covid-19 disease using a SEIHRD dynamical model

2020 ◽  
Author(s):  
Fernando Pazos ◽  
Flavia E. Felicioni
Keyword(s):  
Public Health ◽  
Control Theory ◽  
Ad Hoc ◽  
Parametric Uncertainties ◽  
Social Unrest ◽  
Control Approach ◽  
Health Measures ◽  
Optimal Intensity ◽  
Nonpharmaceutical Interventions ◽  
Proportional Controller

AbstractThe recent worldwide epidemic of Covid-19 disease, for which there is no vaccine or medications to prevent or cure it, led to the adoption of public health measures by governments and populations in most of the affected countries to avoid the contagion and its spread. These measures are known as nonpharmaceutical interventions (NPIs) and their implementation clearly produces social unrest as well as greatly affects the economy. Frequently, NPIs are implemented with an intensity quantified in an ad hoc manner. Control theory offers a worth-while tool for determining the optimal intensity of the NPIs in order to avoid the collapse of the healthcare system while keeping them as low as possible, yielding in a policymakers concrete guidance. We propose here the use of a simple proportional controller that is robust to large parametric uncertainties in the model used.

scholarly journals Excess Mortality in England during the 2019 Summer Heatwaves

Climate ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 14
Author(s):  
Natasha Rustemeyer ◽  
Mark Howells
Keyword(s):  
Public Health ◽  
United Kingdom ◽  
Excess Mortality ◽  
Summer Period ◽  
The Public ◽  
National Statistics ◽  
The United Kingdom ◽  
The Impact ◽  
Excess Deaths ◽  
Related Mortality

There is increasing evidence that rising temperatures and heatwaves in the United Kingdom are associated with an increase in heat-related mortality. However, the Public Health England (PHE) Heatwave mortality monitoring reports, which use provisional death registrations to estimate heat-related mortality in England during heatwaves, have not yet been evaluated. This study aims to retrospectively quantify the impact of heatwaves on mortality during the 2019 summer period using daily death occurrences. Second, using the same method, it quantifies the heat-related mortality for the 2018 and 2017 heatwave periods. Last, it compares the results to the estimated excess deaths for the same period in the PHE Heatwave mortality monitoring reports. The number of cumulative excess deaths during the summer 2019 heatwaves were minimal (161) and were substantially lower than during the summer 2018 heatwaves (1700 deaths) and summer 2017 heatwaves (1489 deaths). All findings were at variance with the PHE Heatwave mortality monitoring reports which estimated cumulative excess deaths to be 892, 863 and 778 during the heatwave periods of 2019, 2018 and 2017, respectively. Issues are identified in the use of provisional death registrations for mortality monitoring and the reduced reliability of the Office for National Statistics (ONS) daily death occurrences database before 2019. These findings may identify more reliable ways to monitor heat mortality during heatwaves in the future.

scholarly journals The Politics of Pandemics: The Effect of Stay-At-Home Orders on COVID-19 Mitigation

2021 ◽  
pp. 1-23
Author(s):  
Shawn Patterson
Keyword(s):  
Public Health ◽  
Party Politics ◽  
Mitigation Strategies ◽  
State Governments ◽  
Synthetic Control ◽  
Social Distancing ◽  
Control Approach ◽  
Contemporary Politics ◽  
Hospital Systems ◽  
At Home

Abstract The COVID-19 pandemic has upended every aspect of American life. State governments responded quickly to protect public health and stabilize overwhelmed hospital systems. The most restrictive policy, the stay-at-home order, was seen by public health officials as a cornerstone of successful state mitigation strategies. But like many aspects of contemporary politics, support for these efforts took on a distinctly partisan hue. In this paper, I argue that party politics significantly affected state policy responses to COVID-19, which in turn limited mitigation efforts. To this point, I first demonstrate that Democratic governors were faster and more likely to adopt stay-at-home orders than Republicans. Next, using a synthetic control approach, I show that these orders caused residents to practice greater social distancing. Finally, I find that greater social distancing worked to “flattened the curve” by limiting the growth of COVID-19 cases. Together these findings show how party politics affected state pandemic responses and have important long-term implications as states begin lifting restrictions.

scholarly journals Use of technology for public health surveillance reporting: opportunities, challenges and lessons learnt from Kenya

2020 ◽  
Author(s):  
Ian Njeru ◽  
David Kareko ◽  
Ngina Kisangau ◽  
Daniel Langat ◽  
Nzisa Liku ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Comparison Group ◽  
Transition Period ◽  
Health Surveillance ◽  
Surveillance Data ◽  
Percentage Points ◽  
Reporting Rates ◽  
The Impact

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.

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