Effective surveillance of non-symptomatic hosts key to preventing local outbreaks during epidemics

Effective surveillance of non-symptomatic hosts key to preventing local outbreaks during epidemics

By Sally Robertson, B.Sc.Nov 9 2020

A team of researchers in the UK and Israel have warned that during infectious disease epidemics such as coronavirus disease 2019 (COVID-19), effective surveillance of non-symptomatic hosts is essential to preventing local outbreaks.

Using COVID-19 as a case study, the team used a “branching process model” to estimate the risk of imported cases leading to local outbreaks in a host population.

The study showed that seeking to only increase surveillance of newly-arrived symptomatic individuals is not an optimal approach to reducing this local outbreak risk.

A strategy that combines increased surveillance of symptomatic cases with efforts to identify and isolate non-symptomatic cases is the most effective approach to reducing this risk, say the researchers.

This combined strategy is the most effective, even when the effort required to identify non-symptomatic cases is much greater than that of the effort required to identify symptomatic cases, they add.

The team – from the University of Oxford, Tel Aviv University, the London School of Hygiene & Tropical Medicine, and Imperial College London – says this highlights the importance of allocating resources to finding non-symptomatic hosts in addition to symptomatic cases during epidemics of infectious disease.

“During epidemics of COVID-19 and other infectious diseases, effective surveillance for non-symptomatic hosts can be crucial to prevent local outbreaks,” say Francesca Anne Lovell-Read and colleagues.

A pre-print version of the research paper is available on the medRxiv* server, while the article undergoes peer review.


Varying the basic reproduction number ��0 from its baseline value (��0 = 3). Plots are analogous to Figure 3D, showing strategies for minimizing the surveillance effort required to achieve a pre-specified risk level (an “acceptable” local outbreak probability). Red dotted lines represent contours along which the probability of a local outbreak is constant, as labelled; red circles indicate the points along these contours at which the total surveillance effort ��7 + ��8 is minimized. The white line indicates the optimal strategy to follow if the pre-specified risk level is reduced. Apart from ��0 and �� (which is changed in each panel to set the value of ��0), all parameters are held fixed at their baseline values given in Table 1. A. ��0 = 1 · 5. B. ��0 = 2. C. ��0 = 2 · 5. D. ��0 = 3 (baseline). E. ��0 = 3 · 5. F. ��

Non-symptomatic hosts present challenges to the surveillance of epidemics

During infectious disease epidemics, two key questions are whether infected cases traveling to new locations will result in local outbreaks and whether surveillance and control interventions in these new locations might reduce this outbreak risk.

During any epidemic, one factor that can hinder surveillance and control interventions is the potential for pre-symptomatic or asymptomatic (referred to here as non-symptomatic) to transmit a pathogen.

“Determining the extent to which non-symptomatic individuals contribute to transmission is essential early in emerging epidemics of a novel pathogen,” writes the team.

Using COVID-19 as a case study to investigate

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In the case of COVID-19, the estimated average incubation period is around five to six days, during which non-symptomatic transmission can occur.

Using COVID-19 as a case-study, Lovell-Read and colleagues used a branching process model to assess the risk of local outbreaks occurring through non-symptomatic transmission among imported cases.

Branching process models are used to assess whether newly arrived cases among a host population will cause a local outbreak and to predict whether potential control measures would be effective.

Under the assumption that imported cases are effectively isolated, the team investigated the effectiveness of surveillance that targets non-symptomatic individuals, symptomatic individuals, or a combination of both groups, when surveillance resources are limited.

What did the study find?

The modeling study showed that increased surveillance of non-symptomatic individuals could be an important contributor to the risk of local outbreaks during epidemics.

“Seeking to increase surveillance of symptomatic hosts alone is typically not the optimal strategy for reducing outbreak risk,” says the team.

The optimal reduction in local outbreak risk was almost always achieved when a combined strategy involving increased surveillance of both symptomatic and non-symptomatic hosts was adopted.

“This remains the case even if the surveillance effort required to find non-symptomatic infected individuals is significantly larger than the effort required to find symptomatic individuals,” writes Lovell-Read and colleagues.

What are the study implications?

“Adopting a strategy that combines an enhancement of surveillance of symptomatic cases with efforts to find and isolate non-symptomatic hosts leads to the largest reduction in the probability that imported cases will initiate a local outbreak,” writes the team.

The researchers add that the findings are expected to apply to epidemics of any pathogen for which non-symptomatic individuals significantly contribute to transmission.

Effective surveillance of non-symptomatic individuals is essential to preventing local outbreaks during COVID-19 epidemics and other infectious disease epidemics, they say.

“Dedicating surveillance resources towards finding non-symptomatic cases can be an important component of public health measures that aim to prevent local outbreaks,” the team concludes.

*Important Notice

medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

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