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

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.

scholarly journals Digital proximity tracing on empirical contact networks for pandemic control

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
G. Cencetti ◽  
G. Santin ◽  
A. Longa ◽  
E. Pigani ◽  
A. Barrat ◽  
...  
Keyword(s):  
Large Scale ◽  
Disease Outbreaks ◽  
Physical Distance ◽  
Contact Tracing ◽  
Reproductive Number ◽  
Modeling Framework ◽  
Infectious Disease Outbreaks ◽  
Contact Patterns ◽  
Contact Data ◽  
The Impact

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.

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

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.

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

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.

scholarly journals Surveillance of acute infectious gastroenteritis (1992–2009) and food-borne disease outbreaks (1996–2009) in Italy, with a focus on the Piedmont and Lombardy regions

2012 ◽  
Vol 17 (8) ◽  
Author(s):  
L Mughini-Gras ◽  
C Graziani ◽  
F Biorci ◽  
A Pavan ◽  
R Magliola ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Disease Outbreaks ◽  
Notification System ◽  
Lombardy Region ◽  
Additional Information ◽  
Regional Systems ◽  
Infectious Gastroenteritis ◽  
Food Borne ◽  
Notification Data ◽  
And Control

We describe trends in the occurrence of acute infectious gastroenteritis (1992 to 2009) and food-borne disease outbreaks (1996 to 2009) in Italy. In 2002, the Piedmont region implemented a surveillance system for early detection and control of food-borne disease outbreaks; in 2004, the Lombardy region implemented a system for surveillance of all notifiable human infectious diseases. Both systems are internet based. We compared the regional figures with the national mean using official notification data provided by the National Infectious Diseases Notification System (SIMI) and the National Institute of Statistics (ISTAT), in order to provide additional information about the epidemiology of these diseases in Italy. When compared with the national mean, data from the two regional systems showed a significant increase in notification rates of non-typhoid salmonellosis and infectious diarrhoea other than non-typhoid salmonellosis, but for food-borne disease outbreaks, the increase was not statistically significant. Although the two regional systems have different objectives and structures, they showed improved sensitivity regarding notification of cases of acute infectious gastroenteritis and, to a lesser extent, food-borne disease outbreaks, and thus provide a more complete picture of the epidemiology of these diseases in Italy.

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

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

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

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.

scholarly journals Optimizing Highly Infectious Disease Isolation Unit Management. Experiences from the Infectious Diseases Isolation and Research Unit, Fort Portal, Uganda

2021 ◽  
pp. 1-17
Author(s):  
Susan Alum ◽  
Moses Asiimwe ◽  
Gerald Kanyomozi ◽  
Jacqueline Nalikka ◽  
Peace Okwaro ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Disease Outbreaks ◽  
Research Unit ◽  
Middle Income ◽  
Human Resource Capacity ◽  
Infectious Disease Outbreaks ◽  
Unit Management ◽  
Resilient Response ◽  
Facility Level ◽  
Resource Capacity

Abstract Infectious disease outbreaks are the scale of the current COVID-19 pandemic are a new phenomenon in many parts of the world. Many isolation unit designs with corresponding workflow dynamics and personal protective equipment postures have been proposed for each emerging disease at the health facility level, depending on the mode of transmission. However, personnel and resource management at the isolation units for a resilient response will vary by human resource capacity, reporting requirements, and practice setting. This paper describes an approach to Isolation unit management at a rural Uganda Hospital and shares lessons from the Uganda experience for isolation unit managers in low- and middle-income settings.

scholarly journals The impact of community containment implementation timing on the spread of COVID-19: A simulation study

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 452 ◽  
Author(s):  
Attayeb Mohsen ◽  
Ahmed Alarabi
Keyword(s):  
Simulation Model ◽  
Disease Outbreaks ◽  
Simulation Method ◽  
Final Outcome ◽  
Disease Spread ◽  
Network Graph ◽  
Real World Data ◽  
Infectious Disease Outbreaks ◽  
Spread Parameters ◽  
The Impact

Background: Community containment is one of the common methods used to mitigate infectious disease outbreaks. The effectiveness of such a method depends on how strictly it is applied and the timing of its implementation. An early start and being strict is very effective; however, at the same time, it impacts freedom and economic opportunity. Here we created a simulation model to understand the effect of the starting day of community containment on the final outcome, that is, the number of those infected, hospitalized and those that died, as we followed the dynamics of COVID-19 pandemic. Methods: We used a stochastic recursive simulation method to apply disease outbreak dynamics measures of COVID-19 as an example to simulate disease spread. Parameters are allowed to be randomly assigned between higher and lower values obtained from published COVID-19 literature. Results: We simulated the dynamics of COVID-19 spread, calculated the number of active infections, hospitalizations and deaths as the outcome of our simulation and compared these results with real world data. We also represented the details of the spread in a network graph structure, and shared the code for the simulation model to be used for examining other variables. Conclusions: Early implementation of community containment has a big impact on the final outcome of an outbreak.

scholarly journals The impact of physician migration on mortality in low and middle-income countries: an economic modelling study

2020 ◽  
Vol 5 (1) ◽  
pp. e001535
Author(s):  
Saurabh Saluja ◽  
Niclas Rudolfson ◽  
Benjamin Ballard Massenburg ◽  
John G Meara ◽  
Mark G Shrime
Keyword(s):  
Low Income ◽  
Excess Mortality ◽  
National Income ◽  
Economic Consequences ◽  
Economic Modelling ◽  
Middle Income ◽  
Physician Migration ◽  
Middle Income Countries ◽  
The Impact ◽  
Low And Middle Income

BackgroundThe WHO estimates a global shortage of 2.8 million physicians, with severe deficiencies especially in low and middle-income countries (LMIC). The unequitable distribution of physicians worldwide is further exacerbated by the migration of physicians from LMICs to high-income countries (HIC). This large-scale migration has numerous economic consequences which include increased mortality associated with inadequate physician supply in LMICs.MethodsWe estimate the economic cost for LMICs due to excess mortality associated with physician migration. To do so, we use the concept of a value of statistical life and marginal mortality benefit provided by physicians. Uncertainty of our estimates is evaluated with Monte Carlo analysis.ResultsWe estimate that LMICs lose US$15.86 billion (95% CI $3.4 to $38.2) annually due to physician migration to HICs. The greatest total costs are incurred by India, Nigeria, Pakistan and South Africa. When these costs are considered as a per cent of gross national income, the cost is greatest in the WHO African region and in low-income countries.ConclusionThe movement of physicians from lower to higher income settings has substantial economic consequences. These are not simply the result of the movement of human capital, but also due to excess mortality associated with loss of physicians. Valuing these costs can inform international and domestic policy discussions that are meant to address this issue.

scholarly journals Measuring excess mortality during the COVID-19 pandemic in low- and lower-middle income countries: the need for mobile phone surveys

2020 ◽  
Author(s):  
Vissého Adjiwanou ◽  
Nurul Alam ◽  
Leontine Alkema ◽  
Gershim Asiki ◽  
Ayaga Bawah ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Low Income ◽  
Excess Mortality ◽  
Mortality Trends ◽  
Monthly Basis ◽  
Middle Income ◽  
Civil Registration ◽  
Middle Income Countries ◽  
Data Gap ◽  
The Impact

In low income and lower-middle income countries, data from civil registration systems do not allow monitoring excess mortality during the COVID-19 pandemic. Rapid mobile phone surveys aimed at measuring mortality trends on a monthly basis are a realistic and safe option for filling that data gap. The data generated by mobile phone surveys can play a key role in better targeting areas or population groups most affected by the pandemic. They can also help monitor the impact of interventions and programs, and rapidly identify what works in mitigating the impact of COVID-19.

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