Back

The Impact of Host-Based Early Warning on Disease Outbreaks

Hernandez, M.; Milechin, L. E.; Davis, S. K.; DeLaura, R.; Claypool, K. T.; Swiston, A.

2020-03-08 epidemiology
10.1101/2020.03.06.20029793 medRxiv
Show abstract

ObjectiveThe detection of communicable pathogens responsible for major outbreaks relies on health care professionals recognition of symptoms manifesting in infectious individuals. Early warning of such communicable diseases before the onset of symptoms could improve both patient care and public health responses. However, the potential impact of such a host-based early warning system on containing the spread of an outbreak and in steering public health response is unknown. MethodsWe extend the deterministic SEIR (Susceptible, Exposed, Infectious, Recovered) model to simulate disease outbreak scenarios and to quantify the potential impact of a host-based early warning capability to mitigate pathogen transmission during an outbreak. In particular, we compare and contrast the performance of five different policies: Self-monitoring and reporting (baseline SEIR model), Quarantining the entire population, Quarantine-on-alert (with high sensitivity early warning), Quarantine-on-alert (with high specificity early warning), and Quarantine-on-alert (ideal early warning). We further evaluate these five policy options against four different outbreak scenarios with high or low disease transmission and high or low initial population exposures. ResultsFor all scenarios, a quarantine-on-alert policy coupled with the near-ideal early warning capability reduces quarantine needs with only a small increase in the number of additional infections. The cost of a highly specific early detection system (i.e., a reduction in false alarms and thus quarantine costs) is an increase in additional infections relative to the near-ideal system. Conversely, a highly sensitive early detection system increases the percentage of the population in quarantine compared to both the ideal and high-specificity early detection system while also reducing the number of additional infections to nearly the numbers seen by quarantining the entire population a priori. ConclusionsOur simulations demonstrate the utility of host-based early warning systems in controlling an outbreak under various outbreak conditions. Our tools also provide a simulation capability for evaluating public health policies enabling quantitative evaluation of their impacts prior to implementation.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
BMC Infectious Diseases
118 papers in training set
Top 0.1%
18.5%
2
PLOS Computational Biology
1633 papers in training set
Top 3%
10.0%
3
Clinical Infectious Diseases
231 papers in training set
Top 0.5%
8.4%
4
PLOS ONE
4510 papers in training set
Top 28%
6.3%
5
BMC Medicine
163 papers in training set
Top 0.6%
6.3%
6
Epidemiology
26 papers in training set
Top 0.1%
4.8%
50% of probability mass above
7
Scientific Reports
3102 papers in training set
Top 37%
3.6%
8
Epidemiology and Infection
84 papers in training set
Top 0.8%
2.6%
9
Epidemics
104 papers in training set
Top 0.6%
2.6%
10
The Journal of Infectious Diseases
182 papers in training set
Top 2%
2.1%
11
Infectious Disease Modelling
50 papers in training set
Top 0.7%
2.1%
12
American Journal of Epidemiology
57 papers in training set
Top 0.6%
1.9%
13
BMC Medical Research Methodology
43 papers in training set
Top 0.5%
1.9%
14
Nature Communications
4913 papers in training set
Top 50%
1.8%
15
International Journal of Epidemiology
74 papers in training set
Top 1%
1.7%
16
The American Journal of Tropical Medicine and Hygiene
60 papers in training set
Top 2%
1.7%
17
BMC Public Health
147 papers in training set
Top 4%
1.7%
18
The Lancet Global Health
24 papers in training set
Top 0.8%
1.1%
19
BMJ Global Health
98 papers in training set
Top 2%
0.9%
20
Frontiers in Public Health
140 papers in training set
Top 8%
0.8%
21
JMIR Public Health and Surveillance
45 papers in training set
Top 4%
0.7%
22
BMJ Open
554 papers in training set
Top 13%
0.7%
23
PeerJ
261 papers in training set
Top 15%
0.7%
24
The Lancet Public Health
20 papers in training set
Top 0.7%
0.7%
25
Eurosurveillance
80 papers in training set
Top 2%
0.6%
26
Open Forum Infectious Diseases
134 papers in training set
Top 3%
0.6%
27
The Lancet Infectious Diseases
71 papers in training set
Top 3%
0.6%
28
Wellcome Open Research
57 papers in training set
Top 3%
0.6%