Overview of the Impact of Epidemic-Assistance Investigations of Foodborne and Other Enteric Disease Outbreaks, 1946-2005

AbstractDigital contact tracing is a relevant tool to control infectious disease outbreaks, including the COVID-19 epidemic. Early work evaluating digital contact tracing omitted important features and heterogeneities of real-world contact patterns influencing contagion dynamics. We fill this gap with a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing in the COVID-19 pandemic. We investigate how well contact tracing apps, coupled with the quarantine of identified contacts, can mitigate the spread in real environments. We find that restrictive policies are more effective in containing the epidemic but come at the cost of unnecessary large-scale quarantines. Policy evaluation through their efficiency and cost results in optimized solutions which only consider contacts longer than 15–20 minutes and closer than 2–3 meters to be at risk. Our results show that isolation and tracing can help control re-emerging outbreaks when some conditions are met: (i) a reduction of the reproductive number through masks and physical distance; (ii) a low-delay isolation of infected individuals; (iii) a high compliance. Finally, we observe the inefficacy of a less privacy-preserving tracing involving second order contacts. Our results may inform digital contact tracing efforts currently being implemented across several countries worldwide.

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Threshold Effects of Infectious Disease Outbreaks on Livestock Prices: Cases of African Swine Fever and Avian Influenza in South Korea

Applied Sciences ◽

10.3390/app11115114 ◽

2021 ◽

Vol 11 (11) ◽

pp. 5114

Author(s):

Hyung-Chul Rah ◽

Hyeon-Woong Kim ◽

Aziz Nasridinov ◽

Wan-Sup Cho ◽

Seo-Hwa Choi ◽

...

Keyword(s):

Avian Influenza ◽

Infectious Diseases ◽

Disease Outbreaks ◽

African Swine Fever ◽

Threshold Effect ◽

Impact Response ◽

Threshold Effects ◽

Infectious Disease Outbreaks ◽

Retail Prices ◽

The Impact

In this paper we demonstrate the threshold effects of infectious diseases on livestock prices. Daily retail prices of pork and chicken were used as structured data; news and SNS mentions of African Swine Fever (ASF) and Avian Influenza (AI) were used as unstructured data. Models were tested for the threshold effects of disease-related news and SNS frequencies, specifically those related to ASF and AI, on the retail prices of pork and chicken, respectively. The effects were found to exist, and the values of ASF-related news on pork prices were estimated to be −9 and 8, indicating that the threshold autoregressive (TAR) model can be divided into three regimes. The coefficients of the ASF-related SNS frequencies on pork prices were 1.1666, 0.2663 and −0.1035 for regimes 1, 2 and 3, respectively, suggesting that pork prices increased by 1.1666 Korean won in regime 1 when ASF-related SNS frequencies increased. To promote pork consumption by SNS posts, the required SNS frequencies were estimated to have impacts as great as one standard deviation in the pork price. These values were 247.057, 1309.158 and 2817.266 for regimes 1, 2 and 3, respectively. The impact response periods for pork prices were estimated to last 48, 6, and 8 days for regimes 1, 2 and 3, respectively. When the prediction accuracies of the TAR and autoregressive (AR) models with regard to pork prices were compared for the root mean square error, the prediction accuracy of the TAR model was found to be slightly better than that of the AR. When the threshold effect of AI-related news on chicken prices was tested, a linear relationship appeared without a threshold effect. These findings suggest that when infectious diseases such as ASF occur for the first time, the impact on livestock prices is significant, as indicated by the threshold effect and the long impact response period. Our findings also suggest that the impact on livestock prices is not remarkable when infectious diseases occur multiple times, as in the case of AI. To date, this study is the first to suggest the use of SNS to promote meat consumption.

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The risk of clinical complications and death among pregnant women with COVID-19 in the Cerner COVID-19 cohort: a retrospective analysis

BMC Pregnancy and Childbirth ◽

10.1186/s12884-021-03772-y ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Fares Qeadan ◽

Nana A. Mensah ◽

Benjamin Tingey ◽

Joseph B. Stanford

Keyword(s):

Pregnant Women ◽

Disease Outbreaks ◽

Hospital Length ◽

Morbidity And Mortality ◽

Hospital Length Of Stay ◽

High Risk Population ◽

Invasive Ventilation ◽

Female Patients ◽

Race Ethnicity ◽

The Impact

Abstract Background Pregnant women are potentially a high-risk population during infectious disease outbreaks such as COVID-19, because of physiologic immune suppression in pregnancy. However, data on the morbidity and mortality of COVID-19 among pregnant women, compared to nonpregnant women, are sparse and inconclusive. We sought to assess the impact of pregnancy on COVID-19 associated morbidity and mortality, with particular attention to the impact of pre-existing comorbidity. Methods We used retrospective data from January through June 2020 on female patients aged 18–44 years old utilizing the Cerner COVID-19 de-identified cohort. We used mixed-effects logistic and exponential regression models to evaluate the risk of hospitalization, maximum hospital length of stay (LOS), moderate ventilation, invasive ventilation, and death for pregnant women while adjusting for age, race/ethnicity, insurance, Elixhauser AHRQ weighted Comorbidity Index, diabetes history, medication, and accounting for clustering of results in similar zip-code regions. Results Out of 22,493 female patients with associated COVID-19, 7.2% (n = 1609) were pregnant. Crude results indicate that pregnant women, compared to non-pregnant women, had higher rates of hospitalization (60.5% vs. 17.0%, P < 0.001), higher mean maximum LOS (0.15 day vs. 0.08 day, P < 0.001) among those who stayed < 1 day, lower mean maximum LOS (2.55 days vs. 3.32 days, P < 0.001) among those who stayed ≥1 day, and higher moderate ventilation use (1.7% vs. 0.7%, P < 0.001) but showed no significant differences in rates of invasive ventilation or death. After adjusting for potentially confounding variables, pregnant women, compared to non-pregnant women, saw higher odds in hospitalization (aOR: 12.26; 95% CI (10.69, 14.06)), moderate ventilation (aOR: 2.35; 95% CI (1.48, 3.74)), higher maximum LOS among those who stayed < 1 day, and lower maximum LOS among those who stayed ≥1 day. No significant associations were found with invasive ventilation or death. For moderate ventilation, differences were seen among age and race/ethnicity groups. Conclusions Among women with COVID-19 disease, pregnancy confers substantial additional risk of morbidity, but no difference in mortality. Knowing these variabilities in the risk is essential to inform decision-makers and guide clinical recommendations for the management of COVID-19 in pregnant women.

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Epidemics and Chinese firms' stock returns: is COVID-19 different?

China Finance Review International ◽

10.1108/cfri-03-2021-0053 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Quang Thi Thieu Nguyen ◽

Dao Le Trang Anh ◽

Christopher Gan

Keyword(s):

Stock Returns ◽

Negative Impact ◽

Stock Exchange ◽

Market Performance ◽

Disease Outbreaks ◽

Stock Exchanges ◽

Content Type ◽

Event Study Method ◽

Economic Shock ◽

The Impact

PurposeThis study investigates the Chinese stocks' returns during different epidemic periods to assess their effects on firms' market performance.Design/methodology/approachThe study employs an event study method on more than 3,000 firms listed on Shanghai and Shenzhen stock exchanges during periods of SARS, H5N1, H7N9 and COVID-19FindingsEpidemics' effect on firms' stock returns is persistent up to 10 days after the event dates. Although the impact varies with types and development of the disease, most firms experience a negative impact of the epidemics. Among the epidemics, COVID-19 has the greatest impact, especially when it grows into a pandemic. The epidemics' impact is uneven across industries. In addition, B-shares and stocks listed on Shanghai Stock Exchange are more negatively influenced by the epidemic than A-shares and those listed on Shenzhen Stock Exchange.Research limitations/implicationsThe results of the study contribute to the limited literature on the effects of disease outbreaks as an economic shock on firm market performance. Given the possibility of other epidemics in the future, the study provides guidance for investors in designing an appropriate investing strategy to cope with the epidemic shocks to the market.Originality/valueThe research is novel in the way it compares and assesses the economic impact of different epidemics on firms and considers their impact at different development stages.

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Impact of the Ebola epidemic on clinical outcomes of HIV-infected soldiers and their dependents in Sierra Leone

International Journal of STD & AIDS ◽

10.1177/0956462418797843 ◽

2018 ◽

Vol 30 (2) ◽

pp. 106-112 ◽

Cited By ~ 3

Author(s):

Elizabeth Nagel ◽

Michael J Blackowicz ◽

Foday Sahr ◽

Olamide D Jarrett

Keyword(s):

Clinical Outcomes ◽

Sierra Leone ◽

Repeated Measures ◽

Disease Outbreaks ◽

Armed Forces ◽

Hiv Treatment ◽

Hiv Care ◽

Increased Risk ◽

The Republic ◽

The Impact

The impact of the 2014–2016 Ebola epidemic in West Africa on human immunodeficiency virus (HIV) treatment in Sierra Leone is unknown, especially for groups with higher HIV prevalence such as the military. Using a retrospective study design, clinical outcomes were evaluated prior to and during the epidemic for 264 HIV-infected soldiers of the Republic of Sierra Leone Armed Forces (RSLAF) and their dependents receiving HIV treatment at the primary RSLAF HIV clinic. Medical records were abstracted for baseline clinical data and clinic attendance. Estimated risk of lost to follow-up (LTFU), default, and number of days without antiretroviral therapy (DWA) were calculated using repeated measures general estimating equations adjusted for age and gender. Due to missing data, 262 patients were included in the final analyses. There was higher risk of LTFU throughout the Ebola epidemic in Sierra Leone compared to the pre-Ebola baseline, with the largest increase in LTFU risk occurring at the peak of the epidemic (relative risk: 3.22, 95% CI: 2.22–4.67). There was an increased risk of default and DWA during the Ebola epidemic for soldiers but not for their dependents. The risk of LTFU, default, and DWA stabilized once the epidemic was largely resolved but remained elevated compared to the pre-Ebola baseline. Our findings demonstrate the negative and potentially lasting impact of the Ebola epidemic on HIV care in Sierra Leone and highlight the need to develop strategies to minimize disruptions in HIV care with future disease outbreaks.

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COVID-19: Examining the case growth-rate due to Visitor vs Local Mobility using Machine Learning: A Study in the United States

10.21203/rs.3.rs-916701/v1 ◽

2021 ◽

Author(s):

satya katragadda ◽

ravi teja bhupatiraju ◽

vijay raghavan ◽

ziad ashkar ◽

raju gottumukkala

Keyword(s):

United States ◽

Machine Learning ◽

Statistical Significance ◽

Disease Outbreaks ◽

The United States ◽

Mobile Phone Data ◽

Infectious Disease Outbreaks ◽

Local Mobility ◽

Local Risk ◽

The Impact

Abstract Background: Travel patterns of humans play a major part in the spread of infectious diseases. This was evident in the geographical spread of COVID-19 in the United States. However, the impact of this mobility and the transmission of the virus due to local travel, compared to the population traveling across state boundaries, is unknown. This study evaluates the impact of local vs. visitor mobility in understanding the growth in the number of cases for infectious disease outbreaks. Methods: We use two different mobility metrics, namely the local risk and visitor risk extracted from trip data generated from anonymized mobile phone data across all 50 states in the United States. We analyzed the impact of just using local trips on infection spread and infection risk potential generated from visitors' trips from various other states. We used the Diebold-Mariano test to compare across three machine learning models. Finally, we compared the performance of models, including visitor mobility for all the three waves in the United States and across all 50 states. Results: We observe that visitor mobility impacts case growth and that including visitor mobility in forecasting the number of COVID-19 cases improves prediction accuracy by 34. We found the statistical significance with respect to the performance improvement resulting from including visitor mobility using the Diebold-Mariano test. We also observe that the significance was much higher during the first peak March to June 2020. Conclusion: With presence of cases everywhere (i.e. local and visitor), visitor mobility (even within the country) is shown to have significant impact on growth in number of cases. While it is not possible to account for other factors such as the impact of interventions, and differences in local mobility and visitor mobility, we find that these observations can be used to plan for both reopening and limiting visitors from regions where there are high number of cases.

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Monitoring for outbreak associated excess mortality in an African city: Detection limits in Antananarivo, Madagascar

10.1101/2020.10.18.20214411 ◽

2020 ◽

Author(s):

Fidisoa Rasambainarivo ◽

Anjarasoa Rasoanomenjanahary ◽

Joelinotahiana Hasina Rabarison ◽

Tanjona Ramiadantsoa ◽

Rila Ratovoson ◽

...

Keyword(s):

Excess Mortality ◽

Disease Outbreaks ◽

African City ◽

Middle Income ◽

Notification System ◽

Infectious Disease Outbreaks ◽

Measles Outbreak ◽

Death Notification ◽

Notification Data ◽

The Impact

AbstractQuantitative estimates of the impact of infectious disease outbreaks are required to develop measured policy responses. In many low- and middle-income countries, inadequate surveillance and incompleteness of death registration are important barriers. Here, we characterize how large an impact on mortality would have to be to be detectable using the uniquely detailed mortality notification data from the city of Antananarivo in Madagascar, with application to a recent measles outbreak. The weekly mortality rate of children during the 2018-2019 measles outbreak was 154% above the expected value at its peak, and the signal can be detected earlier in children than in the general population. This approach to detecting anomalies from expected baseline mortality allows us to delineate the prevalence of COVID-19 at which excess mortality would be detectable with the existing death notification system in the capital of Madagascar. Given current age-specific estimates of the COVID-19 fatality ratio and the age structure of the population in Antananarivo, we estimate that as few as 11 deaths per week in the 60-70 years age group (corresponding to an infection rate of approximately 1%) would detectably exceed the baseline. Data from 2020 will undergo necessary processing and quality control in the coming months. Our results provide a baseline for interpreting this information.

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The Impact of Organisational Characteristics of Staff and Facility on Infectious Disease Outbreaks in Care Homes: a Systematic Review

10.21203/rs.3.rs-861018/v1 ◽

2021 ◽

Author(s):

Ann Liljas ◽

Lenke Morath ◽

Bo Burström ◽

Pär Schön ◽

Janne Agerholm

Keyword(s):

Infectious Disease ◽

Systematic Review ◽

Older People ◽

Disease Outbreaks ◽

Care Homes ◽

Facility Design ◽

Infectious Disease Outbreaks ◽

Facility Size ◽

The Impact ◽

Nurse Aides

Abstract Background: Infectious disease outbreaks are common in care homes, often with substantial impact on the rates of infection and mortality of the residents, who primarily are older people vulnerable to infections. There is growing evidence that organisational characteristics of staff and facility might play a role in infection outbreaks however such evidence have not previously been systematically reviewed. Therefore, this systematic review aims to examine the impact of facility and staff characteristics on the risk of infectious disease outbreaks in care homes.Methods: Five databases were searched. Studies considered for inclusion were of any design reporting on an outbreak of any infectious disease in one or more care homes providing care for primarily older people with original data on: facility size, facility location (urban/rural), facility design, use of temporary hired staff, staff compartmentalizing, residence of staff, and/or nursing aides hours per resident. Retrieved studies were screened, assessed for quality, and analysed employing a narrative synthesis.Results: Sixteen studies (8 cohort studies, 6 cross-sectional studies, 2 case-control) were included from the search which generated 10,424 unique records. COVID-19 was the most commonly reported cause of outbreak (n=11). The other studies focused on influenza, respiratory and gastrointestinal outbreaks. Most studies reported on the impact of facility size (n=11) followed by facility design (n=4), use of temporary hired staff (n=3), facility location (n=2), staff compartmentalizing (n=2), nurse aides hours (n=2) and residence of staff (n=1). Findings suggest that urban location and larger facility size may be associated with greater risks of an infectious outbreak. Additionally, the risk of a larger outbreak seems lower in larger facilities. Whilst staff compartmentalizing may be associated with lower risk of an outbreak, staff residing in highly infected areas may be associated with greater risk of outbreak. The influence of facility design, use of temporary staff, and nurse aides hours remains unclear.Conclusions: This systematic review suggests that larger facilities have greater risks of infectious outbreaks, yet the risk of a larger outbreak seems lower in larger facilities. Due to lack of robust findings the impact of facility and staff characteristics on infectious outbreaks remain largely unknown.PROSPERO: CRD42020213585

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Mental health services for infectious disease outbreaks including COVID-19: a rapid systematic review

Psychological Medicine ◽

10.1017/s0033291720003888 ◽

2020 ◽

Vol 50 (15) ◽

pp. 2498-2513

Author(s):

Jing-Li Yue ◽

Wei Yan ◽

Yan-Kun Sun ◽

Kai Yuan ◽

Si-Zhen Su ◽

...

Keyword(s):

Mental Health ◽

Infectious Disease ◽

Disease Outbreaks ◽

Mental Illnesses ◽

Stepped Care ◽

Research Database ◽

The Public ◽

Infectious Disease Outbreaks ◽

Culturally Adapted ◽

The Impact

AbstractThe upsurge in the number of people affected by the COVID-19 is likely to lead to increased rates of emotional trauma and mental illnesses. This article systematically reviewed the available data on the benefits of interventions to reduce adverse mental health sequelae of infectious disease outbreaks, and to offer guidance for mental health service responses to infectious disease pandemic. PubMed, Web of Science, Embase, PsycINFO, WHO Global Research Database on infectious disease, and the preprint server medRxiv were searched. Of 4278 reports identified, 32 were included in this review. Most articles of psychological interventions were implemented to address the impact of COVID-19 pandemic, followed by Ebola, SARS, and MERS for multiple vulnerable populations. Increasing mental health literacy of the public is vital to prevent the mental health crisis under the COVID-19 pandemic. Group-based cognitive behavioral therapy, psychological first aid, community-based psychosocial arts program, and other culturally adapted interventions were reported as being effective against the mental health impacts of COVID-19, Ebola, and SARS. Culturally-adapted, cost-effective, and accessible strategies integrated into the public health emergency response and established medical systems at the local and national levels are likely to be an effective option to enhance mental health response capacity for the current and for future infectious disease outbreaks. Tele-mental healthcare services were key central components of stepped care for both infectious disease outbreak management and routine support; however, the usefulness and limitations of remote health delivery should also be recognized.

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