Implementation of Power Law Network Models of Epidemic Surveillance Data for Better Evaluation of Outbreak Detection Alarms

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Razvan G. Romanescu ◽  
Rob Deardon
Keyword(s):  
Power Law ◽  
Disease Surveillance ◽  
Incidence Rates ◽  
Rate Of Change ◽  
Outbreak Detection ◽  
Disease Spread ◽  
Infectious Period ◽  
Contact Network ◽  
Human Populations ◽  
Susceptible Population

Abstract Properties of statistical alarms have been well studied for simple disease surveillance models, such as normally distributed incidence rates with a sudden or gradual shift in mean at the start of an outbreak. It is known, however, that outbreak dynamics in human populations depend significantly on the heterogeneity of the underlying contact network. The rate of change in incidence for a disease such as influenza peaks early on during the outbreak, when the most highly connected individuals get infected, and declines as the average number of connections in the remaining susceptible population drops. Alarm systems currently in use for detecting the start of influenza seasons generally ignore this mechanism of disease spread, and, as a result, will miss out on some early warning signals. We investigate the performance of various alarms on epidemics simulated from an undirected network model with a power law degree distribution for a pathogen with a relatively short infectious period. We propose simple custom alarms for the disease system considered, and show that they can detect a change in the process sooner than some traditional alarms. Finally, we test our methods on observed rates of influenza-like illness from two sentinel providers (one French, one Spanish) to illustrate their use in the early detection of the flu season.

scholarly journals Investigating the potential spread of infectious diseases of sheep via agricultural shows in Great Britain

2005 ◽  
Vol 134 (1) ◽  
pp. 31-40 ◽  
Author(s):  
C. R. WEBB
Keyword(s):  
Great Britain ◽  
Infectious Diseases ◽  
Close Contact ◽  
Farm Animal ◽  
Disease Spread ◽  
Infectious Period ◽  
Contact Network ◽  
Spatial Spread ◽  
Animal Populations ◽  
Contact Data

SUMMARYThe rate at which infectious diseases spread through farm animal populations depends both on individual disease characteristics and the opportunity for transmission via close contact. Data on the relationships affecting the contact structure of farm animal populations are, therefore, required to improve mathematical models for the spatial spread of farm animal diseases. This paper presents data on the contact network for agricultural shows in Great Britain, whereby a link between two shows occurs if they share common competitors in the sheep class. Using the network, the potential for disease spread through agricultural shows is investigated varying both the initial show infected and the infectious period of the disease. The analysis reveals a highly connected network such that diseases introduced early in the show season could present a risk to sheep at the majority of subsequent shows. This data emphasizes the importance of maintaining rigorous showground and farm-level bio-security.

scholarly journals Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Meng-Chun Chang ◽  
Rebecca Kahn ◽  
Yu-An Li ◽  
Cheng-Sheng Lee ◽  
Caroline O. Buckee ◽  
...  
Keyword(s):  
Disease Surveillance ◽  
Initial Conditions ◽  
Human Mobility ◽  
Human Movement ◽  
Disease Spread ◽  
Spatial Spread ◽  
Movement Data ◽  
Intercity Travel ◽  
Travel Restrictions ◽  
The Impact

Abstract Background As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. Methods In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. Results We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. Conclusions To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions.

scholarly journals Assessment of the core and support functions of the integrated disease surveillance and response system in Zanzibar, Tanzania

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fatma Saleh ◽  
Jovin Kitau ◽  
Flemming Konradsen ◽  
Leonard E. G. Mboera ◽  
Karin L. Schiøler
Keyword(s):  
Infectious Disease ◽  
Early Detection ◽  
Disease Surveillance ◽  
Health Facilities ◽  
Outbreak Detection ◽  
World Health ◽  
Support Functions ◽  
The Core ◽  
Surveillance And Response ◽  
Facility Level

Abstract Background Disease surveillance is a cornerstone of outbreak detection and control. Evaluation of a disease surveillance system is important to ensure its performance over time. The aim of this study was to assess the performance of the core and support functions of the Zanzibar integrated disease surveillance and response (IDSR) system to determine its capacity for early detection of and response to infectious disease outbreaks. Methods This cross-sectional descriptive study involved 10 districts of Zanzibar and 45 public and private health facilities. A mixed-methods approach was used to collect data. This included document review, observations and interviews with surveillance personnel using a modified World Health Organization generic questionnaire for assessing national disease surveillance systems. Results The performance of the IDSR system in Zanzibar was suboptimal particularly with respect to early detection of epidemics. Weak laboratory capacity at all levels greatly hampered detection and confirmation of cases and outbreaks. None of the health facilities or laboratories could confirm all priority infectious diseases outlined in the Zanzibar IDSR guidelines. Data reporting was weakest at facility level, while data analysis was inadequate at all levels (facility, district and national). The performance of epidemic preparedness and response was generally unsatisfactory despite availability of rapid response teams and budget lines for epidemics in each district. The support functions (supervision, training, laboratory, communication and coordination, human resources, logistic support) were inadequate particularly at the facility level. Conclusions The IDSR system in Zanzibar is weak and inadequate for early detection and response to infectious disease epidemics. The performance of both core and support functions are hampered by several factors including inadequate human and material resources as well as lack of motivation for IDSR implementation within the healthcare delivery system. In the face of emerging epidemics, strengthening of the IDSR system, including allocation of adequate resources, should be a priority in order to safeguard human health and economic stability across the archipelago of Zanzibar.

scholarly journals Modifying the network-based stochastic SEIR model to account for quarantine: an application to COVID-19

2021 ◽  
Vol 10 (s1) ◽  
Author(s):  
Chris Groendyke ◽  
Adam Combs
Keyword(s):  
Network Model ◽  
Transmission Rate ◽  
Disease Spread ◽  
Contact Network ◽  
Model Parameters ◽  
Seir Model ◽  
Disease States ◽  
Potential Contact ◽  
The Mean ◽  
Infectious State

Abstract Objectives: Diseases such as SARS-CoV-2 have novel features that require modifications to the standard network-based stochastic SEIR model. In particular, we introduce modifications to this model to account for the potential changes in behavior patterns of individuals upon becoming symptomatic, as well as the tendency of a substantial proportion of those infected to remain asymptomatic. Methods: Using a generic network model where every potential contact exists with the same common probability, we conduct a simulation study in which we vary four key model parameters (transmission rate, probability of remaining asymptomatic, and the mean lengths of time spent in the exposed and infectious disease states) and examine the resulting impacts on various metrics of epidemic severity, including the effective reproduction number. We then consider the effects of a more complex network model. Results: We find that the mean length of time spent in the infectious state and the transmission rate are the most important model parameters, while the mean length of time spent in the exposed state and the probability of remaining asymptomatic are less important. We also find that the network structure has a significant impact on the dynamics of the disease spread. Conclusions: In this article, we present a modification to the network-based stochastic SEIR epidemic model which allows for modifications to the underlying contact network to account for the effects of quarantine. We also discuss the changes needed to the model to incorporate situations where some proportion of the individuals who are infected remain asymptomatic throughout the course of the disease.

scholarly journals Epidemiological trends in digestive cancers compared to trends in alcohol consumption. Facts from Romania: correlation or coincidence?

2018 ◽  
Vol 91 (4) ◽  
pp. 376-386
Author(s):  
Simona Valean ◽  
Romeo Chira ◽  
Dan Dumitrascu
Keyword(s):  
Alcohol Consumption ◽  
Population Level ◽  
Epidemiological Data ◽  
Epidemiological Studies ◽  
Incidence Rates ◽  
Human Populations ◽  
Causative Relationship ◽  
Consumption Data ◽  
Digestive Cancers ◽  
Epidemiological Trends

Cancer has emerged as the leading cause of death in human populations, according to recent estimations. Epidemiological studies emphasized the role of life style and of environmental factors in promoting the risk for digestive cancers. The contribution of alcohol was highly suspected. Even for digestive cancers with dominant infection etiology, like liver cancer and gastric cancer, the contribution of alcohol should be assessed. At population level there is therefore a need to compare trends in epidemiological data of gastrointestinal cancers and data on alcohol consumption, in order to extrapolate any causative relationship. The purpose of this review was to analyze the time trend of digestive cancers in Romania, in terms of mortality rates (between 1955-2012), and incidence rates (between 2008-2012), in males and females, and to analyze the alcohol consumption data, aiming to find out if there is any association.

scholarly journals Tularemia transmission to humans: a multifaceted surveillance approach

2018 ◽  
Vol 146 (16) ◽  
pp. 2139-2145 ◽  
Author(s):  
N. Akhvlediani ◽  
I. Burjanadze ◽  
D. Baliashvili ◽  
T. Tushishvili ◽  
M. Broladze ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disease Surveillance ◽  
Incidence Rates ◽  
Clinical Factors ◽  
Notifiable Disease ◽  
Surveillance Studies ◽  
Disease Surveillance System ◽  
Acute Infections ◽  
System 2 ◽  
Incident Cases

AbstractTularemia has sustained seroprevalence in Eurasia, with estimates as high as 15% in endemic regions. The purpose of this report is to characterise the current epidemiology of Francisella tularensis subspecies holarctica in Georgia. Three surveillance activities are summarised: (1) acute infections captured in Georgia's notifiable disease surveillance system, (2) infectious disease seroprevalence study of military volunteers, and (3) a study of seroprevalence and risk factors in endemic regions. Descriptive analyses of demographic, exposure and clinical factors were conducted for the surveillance studies; bivariate analyses were computed to identify risk factors of seropositivity using likelihood ratio χ2 tests or Fisher's exact tests. Of the 19 incident cases reported between 2014 and August 2017, 10 were confirmed and nine met the presumptive definition; the estimated annual incidence was 0.12/100 000. The first cases of tularemia in Western Georgia were reported. Seroprevalences of antibodies for F. tularensis were 2.0% for military volunteers and 5.0% for residents in endemic regions. Exposures correlated with seropositivity included work with hay and contact with multiple types of animals. Seroprevalence studies conducted periodically may enhance our understanding of tularemia in countries with dramatically underestimated incidence rates.

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