Leveraging Rich Data and Machine Learning to Facilitate Policy Making on Public Health Interventions in Fighting to Contain the COVID-19 Pandemic

Research Direction ◽

Health Interventions ◽

Mitigation Measures ◽

Short Article ◽

The World ◽

Rich Data

<p>This is a short article, focusing on promoting more study on SEIR modeling by leveraging rich data and machine learning. We believe that this is extremely critical as many regions at the country or state/provincial levels have been struggling with their public health intervention policies on fighting the COVID-19 pandemic. Some recent published papers on mitigation measures show promising SEIR modeling results, which could shred the light for other policymakers at different community levels. We present our perspective on this research direction. Hopefully, we can stimulate more studies and help the world win this “war” against the invisible enemy “coronavirus” sooner rather than later. </p>

Leveraging Rich Data and Machine Learning to Facilitate Policy Making on Public Health Interventions in Fighting to Contain the COVID-19 Pandemic

10.36227/techrxiv.12573755 ◽

2020 ◽

Author(s):

Robin Qiu

Keyword(s):

Public Health ◽

Machine Learning ◽

Research Direction ◽

Health Interventions ◽

Mitigation Measures ◽

Short Article ◽

The World ◽

Rich Data

Strategies and structures for public health interventions

10.1093/med/9780198816805.003.0100 ◽

2021 ◽

pp. 659-684

Author(s):

Sian Griffiths ◽

Kevin A. Fenton

Keyword(s):

Public Health ◽

Monitoring And Evaluation ◽

Health Interventions ◽

Public Health Workforce ◽

The Public ◽

The World ◽

Different Levels ◽

Different Parts

This chapter describes strategies for public health intervention and structures that support them. It uses examples of strategies in different parts of the world and at different levels—global, national, local, and individual—to illustrate various strategic approaches. The key elements of strategy are those of vision, mission, values, aims, plans, and their implementation, monitoring, and evaluation. The examples chosen provide descriptions of how these are articulated and also how interventions are made towards their achievement of better public health. The importance of the way health services are structured, the public health workforce, and underpinning research and use of evidence are emphasized.

Prediction Models for Public Health Containment Measures on COVID-19 Using Artificial Intelligence and Machine Learning: A Systematic Review

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18094499 ◽

2021 ◽

Vol 18 (9) ◽

pp. 4499

Author(s):

Anil Babu Payedimarri ◽

Diego Concina ◽

Luigi Portinale ◽

Massimo Canonico ◽

Deborah Seys ◽

...

Keyword(s):

Public Health ◽

Artificial Intelligence ◽

Machine Learning ◽

Systematic Review ◽

Public Transportation ◽

Prediction Models ◽

Positive Impact ◽

Health Interventions ◽

Commercial Activities

Artificial Intelligence (AI) and Machine Learning (ML) have expanded their utilization in different fields of medicine. During the SARS-CoV-2 outbreak, AI and ML were also applied for the evaluation and/or implementation of public health interventions aimed to flatten the epidemiological curve. This systematic review aims to evaluate the effectiveness of the use of AI and ML when applied to public health interventions to contain the spread of SARS-CoV-2. Our findings showed that quarantine should be the best strategy for containing COVID-19. Nationwide lockdown also showed positive impact, whereas social distancing should be considered to be effective only in combination with other interventions including the closure of schools and commercial activities and the limitation of public transportation. Our findings also showed that all the interventions should be initiated early in the pandemic and continued for a sustained period. Despite the study limitation, we concluded that AI and ML could be of help for policy makers to define the strategies for containing the COVID-19 pandemic.

Accurate spatiotemporal mapping of drug overdose deaths by machine learning of drug-related web-searches

PLoS ONE ◽

10.1371/journal.pone.0243622 ◽

2020 ◽

Vol 15 (12) ◽

pp. e0243622

Author(s):

David S. Campo ◽

Joseph W. Gussler ◽

Amanda Sue ◽

Pavel Skums ◽

Yury Khudyakov

Keyword(s):

Public Health ◽

Machine Learning ◽

Strong Association ◽

The United States ◽

Health Interventions ◽

Morbidity And Mortality ◽

Mortality Trends ◽

Spatiotemporal Mapping ◽

Increased Risk

Persons who inject drugs (PWID) are at increased risk for overdose death (ODD), infections with HIV, hepatitis B (HBV) and hepatitis C virus (HCV), and noninfectious health conditions. Spatiotemporal identification of PWID communities is essential for developing efficient and cost-effective public health interventions for reducing morbidity and mortality associated with injection-drug use (IDU). Reported ODDs are a strong indicator of the extent of IDU in different geographic regions. However, ODD quantification can take time, with delays in ODD reporting occurring due to a range of factors including death investigation and drug testing. This delayed ODD reporting may affect efficient early interventions for infectious diseases. We present a novel model, Dynamic Overdose Vulnerability Estimator (DOVE), for assessment and spatiotemporal mapping of ODDs in different U.S. jurisdictions. Using Google® Web-search volumes (i.e., the fraction of all searches that include certain words), we identified a strong association between the reported ODD rates and drug-related search terms for 2004–2017. A machine learning model (Extremely Random Forest) was developed to produce yearly ODD estimates at state and county levels, as well as monthly estimates at state level. Regarding the total number of ODDs per year, DOVE’s error was only 3.52% (Median Absolute Error, MAE) in the United States for 2005–2017. DOVE estimated 66,463 ODDs out of the reported 70,237 (94.48%) during 2017. For that year, the MAE of the individual ODD rates was 4.43%, 7.34%, and 12.75% among yearly estimates for states, yearly estimates for counties, and monthly estimates for states, respectively. These results indicate suitability of the DOVE ODD estimates for dynamic IDU assessment in most states, which may alert for possible increased morbidity and mortality associated with IDU. ODD estimates produced by DOVE offer an opportunity for a spatiotemporal ODD mapping. Timely identification of potential mortality trends among PWID might assist in developing efficient ODD prevention and HBV, HCV, and HIV infection elimination programs by targeting public health interventions to the most vulnerable PWID communities.

The role of risk communication in public health interventions. An analysis of risk communication for a community quarantine in Germany to curb the SARS-CoV-2 pandemic

PLoS ONE ◽

10.1371/journal.pone.0256113 ◽

2021 ◽

Vol 16 (8) ◽

pp. e0256113

Author(s):

Juliane Scholz ◽

Wibke Wetzker ◽

Annika Licht ◽

Rainer Heintzmann ◽

André Scherag ◽

...

Keyword(s):

Public Health ◽

Risk Communication ◽

Health Interventions ◽

Successful Implementation ◽

Cross Sectional Survey ◽

Cross Sectional ◽

Information Level ◽

Public Health Authorities

Background Separating ill or possibly infectious people from their healthy community is one of the core principles of non-pharmaceutical interventions. However, there is scarce evidence on how to successfully implement quarantine orders. We investigated a community quarantine for an entire village in Germany (Neustadt am Rennsteig, March 2020) with the aim of better understanding the successful implementation of quarantine measures. Methods This cross-sectional survey was conducted in Neustadt am Rennsteig six weeks after the end of a 14-day mandatory community quarantine. The sample size consisted of 562 adults (64% of the community), and the response rate was 295 adults, or 52% (33% of the community). Findings National television was reported as the most important channel of information. Contact with local authorities was very limited, and partners or spouses played a more important role in sharing information. Generally, the self-reported information level was judged to be good (211/289 [73.0%]). The majority of participants (212/289 [73.4%]) approved of the quarantine, and the reported compliance was 217/289 (75.1%). A self-reported higher level of concern as well as a higher level of information correlated positively with both a greater acceptance of quarantine and self-reported compliant behaviour. Interpretation The community quarantine presented a rare opportunity to investigate a public health intervention for an entire community. In order to improve the implementation of public health interventions, public health risk communication activities should be intensified to increase both the information level (potentially leading to better compliance with community quarantine) and the communication level (to facilitate rapport and trust between public health authorities and their communities).

Conceptualizing the Cost of COVID Policy: The Role of Institutional Trade-Offs

The Economists Voice ◽

10.1515/ev-2021-0020 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Vincent Geloso

Keyword(s):

Public Health ◽

Economic History ◽

Health Interventions ◽

Short Article ◽

Trade Offs ◽

Long Run ◽

Institutional Trade ◽

The Cost

Abstract In this short article, I summarize recent research in economic history that suggests long-run institutional trade-offs in public health that affect both health and economic outcomes. These trade-offs suggest that a long timespan is necessary to fully measure the consequences of heavy-handed public health interventions. This timespan means that those who have declared “victory” or “defeat” in the wake of COVID policy are premature. Modesty in terms of policy evaluation and prescription is still warranted.

Adapting Syndromic Surveillance Baselines After Public Health Interventions

Public Health Reports ◽

10.1177/0033354920959080 ◽

2020 ◽

Vol 135 (6) ◽

pp. 737-745

Author(s):

Roger Antony Morbey ◽

Alex James Elliot ◽

Gillian Elizabeth Smith ◽

Andre Charlett

Keyword(s):

Public Health ◽

Syndromic Surveillance ◽

Step Change ◽

Emergency Department Visits ◽

Health Interventions ◽

False Alarms ◽

Rotavirus Vaccine ◽

Before And After

Background Public health surveillance requires historical baselines to identify unusual activity. However, these baselines require adjustment after public health interventions. We describe an example of such an adjustment after the introduction of rotavirus vaccine in England in July 2013. Methods We retrospectively measured the magnitude of differences between baselines and observed counts (residuals) before and after the introduction of a public health intervention, the introduction of a rotavirus vaccine in July 2013. We considered gastroenteritis, diarrhea, and vomiting to be indicators for national syndromic surveillance, including telephone calls to a telehealth system, emergency department visits, and unscheduled consultations with general practitioners. The start of the preintervention period varied depending on the availability of surveillance data: June 2005 for telehealth, November 2009 for emergency departments, and July 2010 for general practitioner data. The postintervention period was July 2013 to the second quarter of 2016. We then determined whether baselines incorporating a step-change reduction or a change in seasonality resulted in more accurate models of activity. Results Residuals in the unadjusted baseline models increased by 42%-198% from preintervention to postintervention. Increases in residuals for vomiting indicators were 19%-44% higher than for diarrhea. Both step-change and seasonality adjustments improved the surveillance models; we found the greatest reduction in residuals in seasonally adjusted models (4%-75%). Conclusion Our results demonstrated the importance of adjusting surveillance baselines after public health interventions, particularly accounting for changes in seasonality. Adjusted baselines produced more representative expected values than did unadjusted baselines, resulting in fewer false alarms and a greater likelihood of detecting public health threats.

Plague and trade in Lagos, 1924–1931

International Journal of Maritime History ◽

10.1177/0843871418765723 ◽

2018 ◽

Vol 30 (2) ◽

pp. 287-301 ◽

Cited By ~ 1

Author(s):

Olukayode A. Faleye

Keyword(s):

Public Health ◽

Economic Policy ◽

Medical Records ◽

Historical Analysis ◽

Health Interventions ◽

Historical Study ◽

Maritime Trade ◽

The Third

The literature on the Third Plague Pandemic in West Africa focuses on urbanisation and disease processes in colonial Senegal, Ghana, and Nigeria. Consequently, there is a dearth of historical study of the relational complexities between public health interventions and maritime trade during the outbreak in the region. It is with this in mind that this article examines the historical effects of plague control on internal commerce and international maritime trade in Lagos from 1924 to 1931. The study is based on the historical analysis of colonial administrative, sanitary and medical records as well as newspaper reports. It concludes that the nature of colonial public health intervention was determined by economic policy preferences that impacted distinctively on internal commerce and international maritime trade in Lagos.

Knowledge, Attitude and Perception of West Africans Towards COVID-19: A Survey to Inform Public Health Intervention

10.21203/rs.3.rs-812134/v1 ◽

2021 ◽

Author(s):

Aniefiok John Udoakang ◽

Alexandra Lindsey Djomkam Zune ◽

Kesego Tapela ◽

Owoicho Oloche ◽

Ifeoluwa Kayode Fagbohun ◽

...

Keyword(s):

Public Health ◽

Online Survey ◽

Preventive Measures ◽

Health Interventions ◽

Basic Knowledge ◽

African Countries ◽

First Case ◽

West Africans

Abstract Background: The first case of the novel coronavirus disease-2019 (COVID-19) in West Africa was first confirmed in Nigeria in February 2020. Since then, several public health interventions and preventive measures have been implemented to curtail transmission of the causative agent, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Therefore, this study was performed to assess the knowledge, attitudes, and perceptions of West Africans towards COVID-19. Methods: An online survey was conducted between 29 September to 29 October 2020 among West Africans. Thirty-three survey questions were designed to collate demographics data and participants’ knowledge, attitude and perception towards COVID-19.Results: Overall, 1106 respondents from 16 West African countries, ranging from 1 to 548 with about 11.8% residing outside the subregion, participated in the survey. The respondents had an average COVID-19 knowledge score of 67.82 ± 8.31, with knowledge of the disease significantly associated with the country of residence (P = 0.00) and marginally so in settlement types (P = 0.05). Most respondents (93.4%) could identify the main COVID-19 symptoms, and 73.20% would consult a healthcare professional if infected with SARS-CoV-2. Also, 75.2% of the respondents are willing to receive the COVID-19 vaccine, whereas 10.40% and 14.40 % are unwilling and undecided, respectively. Perceptions of what constitute COVID-19 preventive measures were highly variable. Approximately, 8% of the respondents felt that their government responded excellently in managing the pandemic while a third felt that the response was just good. Also, more than half (54%) opined that isolation and treatment of COVID-19 patients is a way of curbing SARS-CoV-2 spread.Conclusions: Most West Africans have basic knowledge of COVID-19 and showed a positive attitude, with likely proactive practice towards the disease. However, results showed that these varied across countries and are influenced by the types of settlements. Therefore, the health and education authorities in various countries should develop focused measures capturing people in different settlements to improve their preventative measures when designing public health interventions for COVID-19 and any future epidemics or pandemics.

A case study of the evaluation of a public health intervention

Australian Health Review ◽

10.1071/ah060458 ◽

2006 ◽

Vol 30 (4) ◽

pp. 458 ◽

Cited By ~ 1

Author(s):

Bradley Forssman ◽

Leena Gupta ◽

Graham Burgess

Keyword(s):

Public Health ◽

Disease Outbreaks ◽

Health Interventions ◽

Public Health Action ◽

Infectious Disease Outbreaks ◽

Evaluation Approach ◽

South Wales ◽

Health Action

Large public health interventions to control infectious disease outbreaks are common, but rigorous evaluation to improve the quality and effectiveness of these is rarely undertaken. Following a large community-based clinic to prevent a hepatitis A outbreak, a multifaceted and multidisciplinary evaluation was conducted involving consumers, health professionals and industry partners. The results of this evaluation were used to produce practical operational guidelines for the planning and conduct of future interventions. These guidelines have been distributed to all public health units in New South Wales and may be included in the next edition of the NSW Health notifiable diseases manual. The evaluation approach can be applied to all public health interventions across NSW and Australia to assist in the development of operational guidelines, in order to increase the quality of public health action in outbreak prevention.