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Article ; Online: Aligning staff schedules, testing, and isolation reduces the risk of COVID-19 outbreaks in carceral and other congregate settings: A simulation study.

Hoover, Christopher M / Skaff, Nicholas K / Blumberg, Seth / Fukunaga, Rena

PLOS global public health

2023 Volume 3, Issue 1, Page(s) e0001302

Abstract: COVID-19 outbreaks in congregate settings remain a serious threat to the health of disproportionately affected populations such as people experiencing incarceration or homelessness, the elderly, and essential workers. An individual-based model accounting ...

Abstract	COVID-19 outbreaks in congregate settings remain a serious threat to the health of disproportionately affected populations such as people experiencing incarceration or homelessness, the elderly, and essential workers. An individual-based model accounting for individual infectiousness over time, staff work schedules, and testing and isolation schedules was developed to simulate community transmission of SARS-CoV-2 to staff in a congregate facility and subsequent transmission within the facility that could cause an outbreak. Systematic testing strategies in which staff are tested on the first day of their workweek were found to prevent up to 16% more infections than testing strategies unrelated to staff schedules. Testing staff at the beginning of their workweek, implementing timely isolation following testing, limiting test turnaround time, and increasing test frequency in high transmission scenarios can supplement additional mitigation measures to aid outbreak prevention in congregate settings.
Language	English
Publishing date	2023-01-06
Publishing country	United States
Document type	Journal Article
ISSN	2767-3375
ISSN (online)	2767-3375
DOI	10.1371/journal.pgph.0001302
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Modeling transmission of pathogens in healthcare settings.

Stachel, Anna / Keegan, Lindsay T / Blumberg, Seth

Current opinion in infectious diseases

2021 Volume 34, Issue 4, Page(s) 333–338

Abstract: Purpose of review: Mathematical, statistical, and computational models provide insight into the transmission mechanisms and optimal control of healthcare-associated infections. To contextualize recent findings, we offer a summative review of recent ... ...

Abstract	Purpose of review: Mathematical, statistical, and computational models provide insight into the transmission mechanisms and optimal control of healthcare-associated infections. To contextualize recent findings, we offer a summative review of recent literature focused on modeling transmission of pathogens in healthcare settings. Recent findings: The COVID-19 pandemic has led to a dramatic shift in the modeling landscape as the healthcare community has raced to characterize the transmission dynamics of SARS-CoV-2 and develop effective interventions. Inequities in COVID-19 outcomes have inspired new efforts to quantify how structural bias impacts both health outcomes and model parameterization. Meanwhile, developments in the modeling of methicillin-resistant Staphylococcus aureus, Clostridioides difficile, and other nosocomial infections continue to advance. Machine learning continues to be applied in novel ways, and genomic data is being increasingly incorporated into modeling efforts. Summary: As the type and amount of data continues to grow, mathematical, statistical, and computational modeling will play an increasing role in healthcare epidemiology. Gaps remain in producing models that are generalizable to a variety of time periods, geographic locations, and populations. However, with effective communication of findings and interdisciplinary collaboration, opportunities for implementing models for clinical decision-making and public health decision-making are bound to increase.
MeSH term(s)	COVID-19/epidemiology ; Cross Infection/epidemiology ; Cross Infection/etiology ; Cross Infection/prevention & control ; Cross Infection/transmission ; Disease Outbreaks ; Disease Susceptibility ; Humans ; Machine Learning ; Models, Theoretical ; Pandemics ; Public Health Surveillance
Language	English
Publishing date	2021-05-28
Publishing country	United States
Document type	Journal Article ; Meta-Analysis ; Review
ZDB-ID	645085-4
ISSN	1473-6527 ; 1535-3877 ; 0951-7375 ; 1355-834X
ISSN (online)	1473-6527 ; 1535-3877
ISSN	0951-7375 ; 1355-834X
DOI	10.1097/QCO.0000000000000742
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 2462: Show issues

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Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

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Article ; Online: Challenges in Forecasting Antimicrobial Resistance.

Pei, Sen / Blumberg, Seth / Vega, Jaime Cascante / Robin, Tal / Zhang, Yue / Medford, Richard J / Adhikari, Bijaya / Shaman, Jeffrey

Emerging infectious diseases

2023 Volume 29, Issue 4, Page(s) 679–685

Abstract: Antimicrobial resistance is a major threat to human health. Since the 2000s, computational tools for predicting infectious diseases have been greatly advanced; however, efforts to develop real-time forecasting models for antimicrobial-resistant organisms ...

Abstract	Antimicrobial resistance is a major threat to human health. Since the 2000s, computational tools for predicting infectious diseases have been greatly advanced; however, efforts to develop real-time forecasting models for antimicrobial-resistant organisms (AMROs) have been absent. In this perspective, we discuss the utility of AMRO forecasting at different scales, highlight the challenges in this field, and suggest future research priorities. We also discuss challenges in scientific understanding, access to high-quality data, model calibration, and implementation and evaluation of forecasting models. We further highlight the need to initiate research on AMRO forecasting using currently available data and resources to galvanize the research community and address initial practical questions.
MeSH term(s)	Humans ; Anti-Bacterial Agents/pharmacology ; Anti-Bacterial Agents/therapeutic use ; Drug Resistance, Bacterial ; Communicable Diseases ; Forecasting ; Data Accuracy
Chemical Substances	Anti-Bacterial Agents
Language	English
Publishing date	2023-03-21
Publishing country	United States
Document type	Journal Article ; Review ; Research Support, U.S. Gov't, P.H.S.
ZDB-ID	1380686-5
ISSN	1080-6059 ; 1080-6040
ISSN (online)	1080-6059
ISSN	1080-6040
DOI	10.3201/eid2904.221552
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 4778: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

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Article: Rates of SARS-CoV-2 transmission between and into California state prisons.

Dubey, Preeti / Hoover, Christopher M / Lu, Phoebe / Blumberg, Seth / Porco, Travis C / Parsons, Todd L / Worden, Lee

medRxiv : the preprint server for health sciences

2023

Abstract: Correctional institutions are a crucial hotspot amplifying SARS-CoV-2 spread and disease disparity in the U.S. In the California state prison system, multiple massive outbreaks have been caused by transmission between prisons. Correctional staff are a ... ...

Abstract	Correctional institutions are a crucial hotspot amplifying SARS-CoV-2 spread and disease disparity in the U.S. In the California state prison system, multiple massive outbreaks have been caused by transmission between prisons. Correctional staff are a likely vector for transmission into the prison system from surrounding communities. We used publicly available data to estimate the magnitude of flows to and between California state prisons, estimating rates of transmission from communities to prison staff and residents, among and between residents and staff within facilities, and between staff and residents of distinct facilities in the state's 34 prisons through March 22, 2021. We use a mechanistic model, the Hawkes process, reflecting the dynamics of SARS-CoV-2 transmission, for joint estimation of transmission rates. Using nested models for hypothesis testing, we compared the results to simplified models (i) without transmission between prisons, and (ii) with no distinction between prison staff and residents. We estimated that transmission between different facilities' staff is a significant cause of disease spread, and that staff are a vector of transmission between resident populations and outside communities. While increased screening and vaccination of correctional staff may help reduce introductions, large-scale decarceration remains crucially needed as more limited measures are not likely to prevent large-scale disease spread.
Language	English
Publishing date	2023-08-25
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.08.24.23294583
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Developing a COVID-19 WHO Clinical Progression Scale inpatient database from electronic health record data.

Ramaswamy, Priya / Gong, Jen J / Saleh, Sameh N / McDonald, Samuel A / Blumberg, Seth / Medford, Richard J / Liu, Xinran

Journal of the American Medical Informatics Association : JAMIA

2022 Volume 29, Issue 7, Page(s) 1279–1285

Abstract: Objective: There is a need for a systematic method to implement the World Health Organization's Clinical Progression Scale (WHO-CPS), an ordinal clinical severity score for coronavirus disease 2019 patients, to electronic health record (EHR) data. We ... ...

Abstract	Objective: There is a need for a systematic method to implement the World Health Organization's Clinical Progression Scale (WHO-CPS), an ordinal clinical severity score for coronavirus disease 2019 patients, to electronic health record (EHR) data. We discuss our process of developing guiding principles mapping EHR data to WHO-CPS scores across multiple institutions. Materials and methods: Using WHO-CPS as a guideline, we developed the technical blueprint to map EHR data to ordinal clinical severity scores. We applied our approach to data from 2 medical centers. Results: Our method was able to classify clinical severity for 100% of patient days for 2756 patient encounters across 2 institutions. Discussion: Implementing new clinical scales can be challenging; strong understanding of health system data architecture was integral to meet the clinical intentions of the WHO-CPS. Conclusion: We describe a detailed blueprint for how to apply the WHO-CPS scale to patient data from the EHR.
MeSH term(s)	COVID-19 ; Databases, Factual ; Electronic Health Records ; Humans ; Inpatients ; World Health Organization
Language	English
Publishing date	2022-03-15
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, P.H.S.
ZDB-ID	1205156-1
ISSN	1527-974X ; 1067-5027
ISSN (online)	1527-974X
ISSN	1067-5027
DOI	10.1093/jamia/ocac041
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 4128: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MO 312: Show issues

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Article ; Online: Modeling scenarios for mitigating outbreaks in congregate settings.

Blumberg, Seth / Lu, Phoebe / Kwan, Ada T / Hoover, Christopher M / Lloyd-Smith, James O / Sears, David / Bertozzi, Stefano M / Worden, Lee

PLoS computational biology

2022 Volume 18, Issue 7, Page(s) e1010308

Abstract: The explosive outbreaks of COVID-19 seen in congregate settings such as prisons and nursing homes, has highlighted a critical need for effective outbreak prevention and mitigation strategies for these settings. Here we consider how different types of ... ...

Abstract	The explosive outbreaks of COVID-19 seen in congregate settings such as prisons and nursing homes, has highlighted a critical need for effective outbreak prevention and mitigation strategies for these settings. Here we consider how different types of control interventions impact the expected number of symptomatic infections due to outbreaks. Introduction of disease into the resident population from the community is modeled as a stochastic point process coupled to a branching process, while spread between residents is modeled via a deterministic compartmental model that accounts for depletion of susceptible individuals. Control is modeled as a proportional decrease in the number of susceptible residents, the reproduction number, and/or the proportion of symptomatic infections. This permits a range of assumptions about the density dependence of transmission and modes of protection by vaccination, depopulation and other types of control. We find that vaccination or depopulation can have a greater than linear effect on the expected number of cases. For example, assuming a reproduction number of 3.0 with density-dependent transmission, we find that preemptively reducing the size of the susceptible population by 20% reduced overall disease burden by 47%. In some circumstances, it may be possible to reduce the risk and burden of disease outbreaks by optimizing the way a group of residents are apportioned into distinct residential units. The optimal apportionment may be different depending on whether the goal is to reduce the probability of an outbreak occurring, or the expected number of cases from outbreak dynamics. In other circumstances there may be an opportunity to implement reactive disease control measures in which the number of susceptible individuals is rapidly reduced once an outbreak has been detected to occur. Reactive control is most effective when the reproduction number is not too high, and there is minimal delay in implementing control. We highlight the California state prison system as an example for how these findings provide a quantitative framework for understanding disease transmission in congregate settings. Our approach and accompanying interactive website (https://phoebelu.shinyapps.io/DepopulationModels/) provides a quantitative framework to evaluate the potential impact of policy decisions governing infection control in outbreak settings.
MeSH term(s)	COVID-19/epidemiology ; COVID-19/prevention & control ; Disease Outbreaks/prevention & control ; Humans ; Infection Control ; Nursing Homes ; Vaccination
Language	English
Publishing date	2022-07-20
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, P.H.S. ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1010308
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Assessing the plausibility of subcritical transmission of 2019-nCoV in the United States

Blumberg, Seth / Lietman, Thomas M / Porco, Travis C

Abstract: Abstract: The 2019-nCoV outbreak has raised concern of global spread. While person-to-person transmission within the Wuhan district has led to a large outbreak, the transmission potential outside of the region remains unclear. Here we present a simple ... ...

Abstract	Abstract: The 2019-nCoV outbreak has raised concern of global spread. While person-to-person transmission within the Wuhan district has led to a large outbreak, the transmission potential outside of the region remains unclear. Here we present a simple approach for determining whether the upper limit of the confidence interval for the reproduction number exceeds one for transmission in the United States, which would allow endemic transmission. As of February 7, 2020, the number of cases in the United states support subcritical transmission, rather than ongoing transmission. However, this conclusion can change if pre-symptomatic cases resulting from human-to-human transmission have not yet been identified.
Keywords	covid19
Publisher	MedRxiv; WHO
Document type	Article ; Online
DOI	10.1101/2020.02.08.20021311
Database	COVID19

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Article ; Online: Assessing the plausibility of subcritical transmission of 2019-nCoV in the United States

Blumberg, Seth / Lietman, Thomas M / Porco, Travis C

medRxiv

Abstract	Abstract: The 2019-nCoV outbreak has raised concern of global spread. While person-to-person transmission within the Wuhan district has led to a large outbreak, the transmission potential outside of the region remains unclear. Here we present a simple approach for determining whether the upper limit of the confidence interval for the reproduction number exceeds one for transmission in the United States, which would allow endemic transmission. As of February 7, 2020, the number of cases in the United states support subcritical transmission, rather than ongoing transmission. However, this conclusion can change if pre-symptomatic cases resulting from human-to-human transmission have not yet been identified.
Keywords	covid19
Language	English
Publishing date	2020-02-11
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2020.02.08.20021311
Database	COVID19

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Article ; Online: Aligning staffing schedules with testing and isolation strategies reduces the risk of COVID-19 outbreaks in carceral and other congregate settings: A simulation study

Hoover, Christopher M / Skaff, Nicholas K / Blumberg, Seth / Fukunaga, Rena

medRxiv

Abstract	COVID-19 outbreaks in congregate settings remain a serious threat to the health of disproportionately affected populations such as people experiencing incarceration or homelessness, the elderly, and essential workers. An individual-based model accounting for individual infectiousness over time, staff work schedules, and testing and isolation schedules was developed to simulate community transmission of SARS-CoV-2 to staff in a congregate facility and subsequent transmission within the facility that could cause an outbreak. Systematic testing strategies in which staff are tested on the first day of their workweek were found to prevent up to 16% more transmission events than testing strategies unrelated to staff schedules. Testing staff at the beginning of their workweek, implementing timely isolation following testing, limiting test turnaround time, and increasing test frequency in high transmission scenarios can supplement additional mitigation measures to aid outbreak prevention in congregate settings.
Keywords	covid19
Language	English
Publishing date	2021-10-25
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2021.10.22.21265396
Database	COVID19

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Article: Estimation of effects of contact tracing and mask adoption on COVID-19 transmission in San Francisco: a modeling study.

Worden, Lee / Wannier, Rae / Blumberg, Seth / Ge, Alex Y / Rutherford, George W / Porco, Travis C

medRxiv : the preprint server for health sciences

2020

Abstract: The current COVID-19 pandemic has spurred concern about what interventions may be effective at reducing transmission. The city and county of San Francisco imposed a shelter-in-place order in March 2020, followed by use of a contact tracing program and a ... ...

Abstract	The current COVID-19 pandemic has spurred concern about what interventions may be effective at reducing transmission. The city and county of San Francisco imposed a shelter-in-place order in March 2020, followed by use of a contact tracing program and a policy requiring use of cloth face masks. We used statistical estimation and simulation to estimate the effectiveness of these interventions in San Francisco. We estimated that self-isolation and other practices beginning at the time of San Francisco's shelter-in-place order reduced the effective reproduction number of COVID-19 by 35.4% (95% CI, -20.1%-81.4%). We estimated the effect of contact tracing on the effective reproduction number to be a reduction of approximately 44% times the fraction of cases that are detected, which may be modest if the detection rate is low. We estimated the impact of cloth mask adoption on reproduction number to be approximately 8.6%, and note that the benefit of mask adoption may be substantially greater for essential workers and other vulnerable populations, residents return to circulating outside the home more often. We estimated the effect of those interventions on incidence by simulating counterfactual scenarios in which contact tracing was not adopted, cloth masks were not adopted, and neither contact tracing nor cloth masks was adopted, and found increases in case counts that were modest, but relatively larger than the effects on reproduction numbers. These estimates and model results suggest that testing coverage and timing of testing and contact tracing may be important, and that modest effects on reproduction numbers can nonetheless cause substantial effects on case counts over time.
Keywords	covid19
Language	English
Publishing date	2020-06-11
Publishing country	United States
Document type	Preprint
DOI	10.1101/2020.06.09.20125831
Database	MEDical Literature Analysis and Retrieval System OnLINE

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