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Using modelling to disentangle the relative contributions of zoonotic and anthroponotic transmission: the case of lassa fever.

Lo Iacono G, Cunningham AA, Fichet-Calvet E, Garry RF, Grant DS, Khan SH, Leach M, Moses LM, Schieffelin JS, Shaffer JG, Webb CT, Wood JL - PLoS Negl Trop Dis (2015)

Bottom Line: Zoonotic infections, which transmit from animals to humans, form the majority of new human pathogens.Indeed, large hospital-related outbreaks have been reported.However, we found much of this transmission is associated with a disproportionally large impact of a few individuals ('super-spreaders'), as we found only [Formula: see text] of human cases result in an effective reproduction number (i.e. the average number of secondary cases per infectious case) [Formula: see text], with a maximum value up to [Formula: see text].

View Article: PubMed Central - PubMed

Affiliation: Department of Veterinary Medicine, Disease Dynamics Unit, University of Cambridge, Cambridge, United Kingdom.

ABSTRACT

Background: Zoonotic infections, which transmit from animals to humans, form the majority of new human pathogens. Following zoonotic transmission, the pathogen may already have, or may acquire, the ability to transmit from human to human. With infections such as Lassa fever (LF), an often fatal, rodent-borne, hemorrhagic fever common in areas of West Africa, rodent-to-rodent, rodent-to-human, human-to-human and even human-to-rodent transmission patterns are possible. Indeed, large hospital-related outbreaks have been reported. Estimating the proportion of transmission due to human-to-human routes and related patterns (e.g. existence of super-spreaders), in these scenarios is challenging, but essential for planned interventions.

Methodology/principal findings: Here, we make use of an innovative modeling approach to analyze data from published outbreaks and the number of LF hospitalized patients to Kenema Government Hospital in Sierra Leone to estimate the likely contribution of human-to-human transmission. The analyses show that almost [Formula: see text] of the cases at KGH are secondary cases arising from human-to-human transmission. However, we found much of this transmission is associated with a disproportionally large impact of a few individuals ('super-spreaders'), as we found only [Formula: see text] of human cases result in an effective reproduction number (i.e. the average number of secondary cases per infectious case) [Formula: see text], with a maximum value up to [Formula: see text].

Conclusions/significance: This work explains the discrepancy between the sizes of reported LF outbreaks and a clinical perception that human-to-human transmission is low. Future assessment of risks of LF and infection control guidelines should take into account the potentially large impact of super-spreaders in human-to-human transmission. Our work highlights several neglected topics in LF research, the occurrence and nature of super-spreading events and aspects of social behavior in transmission and detection.

No MeSH data available.


Related in: MedlinePlus

Impact of super-spreaders II.A: proportion of cases when the individual effective reproduction number  is greater than one. (i.e. the ratio of the cardinalities of  and , where  is set of all simulated  and  the subset of cases when  is greater than one). B: the expected, relative number of cases generated by this proportion. (i.e. the fraction of the areas of )
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pntd-0003398-g006: Impact of super-spreaders II.A: proportion of cases when the individual effective reproduction number is greater than one. (i.e. the ratio of the cardinalities of and , where is set of all simulated and the subset of cases when is greater than one). B: the expected, relative number of cases generated by this proportion. (i.e. the fraction of the areas of )

Mentions: A simple approach to evaluate the risk of super-spreaders is to invoke the so-called ‘20/80 rule’ (whereby of cases cause of transmission, see [45], [46]). To this end, for different values of the contribution of human-to-human transmission, , we calculated i) the proportion of cases when (Fig. 6.A), and ii) its proportional impact, given by the expected, relative number of secondary cases generated by this proportion (see Fig. 6.B for further explanations); the maximum in the simulations was also recorded. For a contribution of human-to-human transmission in the region of , only of realizations gave , but they are, on average, responsible for of secondary cases, with a maximum . In an extreme situation, when the disease is transmitted only by humans, of cases are responsible for the of secondary cases with a maximum up to , which resembles the ‘20/80 rule’.


Using modelling to disentangle the relative contributions of zoonotic and anthroponotic transmission: the case of lassa fever.

Lo Iacono G, Cunningham AA, Fichet-Calvet E, Garry RF, Grant DS, Khan SH, Leach M, Moses LM, Schieffelin JS, Shaffer JG, Webb CT, Wood JL - PLoS Negl Trop Dis (2015)

Impact of super-spreaders II.A: proportion of cases when the individual effective reproduction number  is greater than one. (i.e. the ratio of the cardinalities of  and , where  is set of all simulated  and  the subset of cases when  is greater than one). B: the expected, relative number of cases generated by this proportion. (i.e. the fraction of the areas of )
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4288732&req=5

pntd-0003398-g006: Impact of super-spreaders II.A: proportion of cases when the individual effective reproduction number is greater than one. (i.e. the ratio of the cardinalities of and , where is set of all simulated and the subset of cases when is greater than one). B: the expected, relative number of cases generated by this proportion. (i.e. the fraction of the areas of )
Mentions: A simple approach to evaluate the risk of super-spreaders is to invoke the so-called ‘20/80 rule’ (whereby of cases cause of transmission, see [45], [46]). To this end, for different values of the contribution of human-to-human transmission, , we calculated i) the proportion of cases when (Fig. 6.A), and ii) its proportional impact, given by the expected, relative number of secondary cases generated by this proportion (see Fig. 6.B for further explanations); the maximum in the simulations was also recorded. For a contribution of human-to-human transmission in the region of , only of realizations gave , but they are, on average, responsible for of secondary cases, with a maximum . In an extreme situation, when the disease is transmitted only by humans, of cases are responsible for the of secondary cases with a maximum up to , which resembles the ‘20/80 rule’.

Bottom Line: Zoonotic infections, which transmit from animals to humans, form the majority of new human pathogens.Indeed, large hospital-related outbreaks have been reported.However, we found much of this transmission is associated with a disproportionally large impact of a few individuals ('super-spreaders'), as we found only [Formula: see text] of human cases result in an effective reproduction number (i.e. the average number of secondary cases per infectious case) [Formula: see text], with a maximum value up to [Formula: see text].

View Article: PubMed Central - PubMed

Affiliation: Department of Veterinary Medicine, Disease Dynamics Unit, University of Cambridge, Cambridge, United Kingdom.

ABSTRACT

Background: Zoonotic infections, which transmit from animals to humans, form the majority of new human pathogens. Following zoonotic transmission, the pathogen may already have, or may acquire, the ability to transmit from human to human. With infections such as Lassa fever (LF), an often fatal, rodent-borne, hemorrhagic fever common in areas of West Africa, rodent-to-rodent, rodent-to-human, human-to-human and even human-to-rodent transmission patterns are possible. Indeed, large hospital-related outbreaks have been reported. Estimating the proportion of transmission due to human-to-human routes and related patterns (e.g. existence of super-spreaders), in these scenarios is challenging, but essential for planned interventions.

Methodology/principal findings: Here, we make use of an innovative modeling approach to analyze data from published outbreaks and the number of LF hospitalized patients to Kenema Government Hospital in Sierra Leone to estimate the likely contribution of human-to-human transmission. The analyses show that almost [Formula: see text] of the cases at KGH are secondary cases arising from human-to-human transmission. However, we found much of this transmission is associated with a disproportionally large impact of a few individuals ('super-spreaders'), as we found only [Formula: see text] of human cases result in an effective reproduction number (i.e. the average number of secondary cases per infectious case) [Formula: see text], with a maximum value up to [Formula: see text].

Conclusions/significance: This work explains the discrepancy between the sizes of reported LF outbreaks and a clinical perception that human-to-human transmission is low. Future assessment of risks of LF and infection control guidelines should take into account the potentially large impact of super-spreaders in human-to-human transmission. Our work highlights several neglected topics in LF research, the occurrence and nature of super-spreading events and aspects of social behavior in transmission and detection.

No MeSH data available.


Related in: MedlinePlus