Limits...
Detecting differential transmissibilities that affect the size of self-limited outbreaks.

Blumberg S, Funk S, Pulliam JR - PLoS Pathog. (2014)

Bottom Line: Our analysis is based on a branching process model that permits statistical comparison of both the strength and heterogeneity of transmission for two distinct types of cases.When applied to chain size data for MERS-CoV transmission before 2014, our method indicates that despite an apparent trend towards improved control, there is not enough statistical evidence to indicate that R eff has declined with time.Human monkeypox, on the other hand, does not show evidence of differential transmission between animals in contact with humans, primary cases, or secondary cases, which assuages the concern that social mixing can amplify transmission by secondary cases.

View Article: PubMed Central - PubMed

Affiliation: Francis I. Proctor Foundation, University of California San Francisco, San Francisco, California, United States of America; Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.

ABSTRACT
Our ability to respond appropriately to infectious diseases is enhanced by identifying differences in the potential for transmitting infection between individuals. Here, we identify epidemiological traits of self-limited infections (i.e. infections with an effective reproduction number satisfying [0 < R eff < 1) that correlate with transmissibility. Our analysis is based on a branching process model that permits statistical comparison of both the strength and heterogeneity of transmission for two distinct types of cases. Our approach provides insight into a variety of scenarios, including the transmission of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in the Arabian peninsula, measles in North America, pre-eradication smallpox in Europe, and human monkeypox in the Democratic Republic of the Congo. When applied to chain size data for MERS-CoV transmission before 2014, our method indicates that despite an apparent trend towards improved control, there is not enough statistical evidence to indicate that R eff has declined with time. Meanwhile, chain size data for measles in the United States and Canada reveal statistically significant geographic variation in R eff, suggesting that the timing and coverage of national vaccination programs, as well as contact tracing procedures, may shape the size distribution of observed infection clusters. Infection source data for smallpox suggests that primary cases transmitted more than secondary cases, and provides a quantitative assessment of the effectiveness of control interventions. Human monkeypox, on the other hand, does not show evidence of differential transmission between animals in contact with humans, primary cases, or secondary cases, which assuages the concern that social mixing can amplify transmission by secondary cases. Lastly, we evaluate surveillance requirements for detecting a change in the human-to-human transmission of monkeypox since the cessation of cross-protective smallpox vaccination. Our studies lay the foundation for future investigations regarding how infection source, vaccination status or other putative transmissibility traits may affect self-limited transmission.

No MeSH data available.


Related in: MedlinePlus

Comparing the transmissibility of primary and secondary cases for smallpox in Europe, 1958–1973.The layout is analogous to Figure 2 except the axes distinguish between transmission of primary and secondary cases. The inset of panel A replicates the results when  and  are inferred separately (our preferred model), except that the y-axis is now the ratio of  to . For panels B and C, the data is shown only for cases where there was a clear record of subsequent secondary infections (as opposed to knowing that four cases lead to ten secondary cases in aggregate). The 95% confidence intervals were found by parametric bootstrap on this more limited data set.
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ppat-1004452-g004: Comparing the transmissibility of primary and secondary cases for smallpox in Europe, 1958–1973.The layout is analogous to Figure 2 except the axes distinguish between transmission of primary and secondary cases. The inset of panel A replicates the results when and are inferred separately (our preferred model), except that the y-axis is now the ratio of to . For panels B and C, the data is shown only for cases where there was a clear record of subsequent secondary infections (as opposed to knowing that four cases lead to ten secondary cases in aggregate). The 95% confidence intervals were found by parametric bootstrap on this more limited data set.

Mentions: Smallpox clusters were tabulated according to the number of cases in each generation of spread [12]. The inference results indicate that secondary cases transmitted significantly less than primary cases (seen by the lack of overlap of contours with the grey line in Figure 4 and by the statistical selection of the non-restricted model in Table 3). In fact, the effectiveness of control procedures can be quantified by looking at the ratio of reproduction numbers for primary and secondary transmission (Figure 4 inset). The ratio of the maximum likelihood values for to suggests that control reduced by 75%. Meanwhile, for both primary and secondary transmission, a high degree of transmission heterogeneity is evident (since the MLE estimates of and are substantially less than one and the value of the model is large). Based on selection of the unrestricted model, and the associated estimates of , there appears to be significantly more heterogeneity of disease transmission for secondary cases than for primary cases. The type I error for this analysis was estimated to be 5.1% by parametric bootstrapping.


Detecting differential transmissibilities that affect the size of self-limited outbreaks.

Blumberg S, Funk S, Pulliam JR - PLoS Pathog. (2014)

Comparing the transmissibility of primary and secondary cases for smallpox in Europe, 1958–1973.The layout is analogous to Figure 2 except the axes distinguish between transmission of primary and secondary cases. The inset of panel A replicates the results when  and  are inferred separately (our preferred model), except that the y-axis is now the ratio of  to . For panels B and C, the data is shown only for cases where there was a clear record of subsequent secondary infections (as opposed to knowing that four cases lead to ten secondary cases in aggregate). The 95% confidence intervals were found by parametric bootstrap on this more limited data set.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4214794&req=5

ppat-1004452-g004: Comparing the transmissibility of primary and secondary cases for smallpox in Europe, 1958–1973.The layout is analogous to Figure 2 except the axes distinguish between transmission of primary and secondary cases. The inset of panel A replicates the results when and are inferred separately (our preferred model), except that the y-axis is now the ratio of to . For panels B and C, the data is shown only for cases where there was a clear record of subsequent secondary infections (as opposed to knowing that four cases lead to ten secondary cases in aggregate). The 95% confidence intervals were found by parametric bootstrap on this more limited data set.
Mentions: Smallpox clusters were tabulated according to the number of cases in each generation of spread [12]. The inference results indicate that secondary cases transmitted significantly less than primary cases (seen by the lack of overlap of contours with the grey line in Figure 4 and by the statistical selection of the non-restricted model in Table 3). In fact, the effectiveness of control procedures can be quantified by looking at the ratio of reproduction numbers for primary and secondary transmission (Figure 4 inset). The ratio of the maximum likelihood values for to suggests that control reduced by 75%. Meanwhile, for both primary and secondary transmission, a high degree of transmission heterogeneity is evident (since the MLE estimates of and are substantially less than one and the value of the model is large). Based on selection of the unrestricted model, and the associated estimates of , there appears to be significantly more heterogeneity of disease transmission for secondary cases than for primary cases. The type I error for this analysis was estimated to be 5.1% by parametric bootstrapping.

Bottom Line: Our analysis is based on a branching process model that permits statistical comparison of both the strength and heterogeneity of transmission for two distinct types of cases.When applied to chain size data for MERS-CoV transmission before 2014, our method indicates that despite an apparent trend towards improved control, there is not enough statistical evidence to indicate that R eff has declined with time.Human monkeypox, on the other hand, does not show evidence of differential transmission between animals in contact with humans, primary cases, or secondary cases, which assuages the concern that social mixing can amplify transmission by secondary cases.

View Article: PubMed Central - PubMed

Affiliation: Francis I. Proctor Foundation, University of California San Francisco, San Francisco, California, United States of America; Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.

ABSTRACT
Our ability to respond appropriately to infectious diseases is enhanced by identifying differences in the potential for transmitting infection between individuals. Here, we identify epidemiological traits of self-limited infections (i.e. infections with an effective reproduction number satisfying [0 < R eff < 1) that correlate with transmissibility. Our analysis is based on a branching process model that permits statistical comparison of both the strength and heterogeneity of transmission for two distinct types of cases. Our approach provides insight into a variety of scenarios, including the transmission of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in the Arabian peninsula, measles in North America, pre-eradication smallpox in Europe, and human monkeypox in the Democratic Republic of the Congo. When applied to chain size data for MERS-CoV transmission before 2014, our method indicates that despite an apparent trend towards improved control, there is not enough statistical evidence to indicate that R eff has declined with time. Meanwhile, chain size data for measles in the United States and Canada reveal statistically significant geographic variation in R eff, suggesting that the timing and coverage of national vaccination programs, as well as contact tracing procedures, may shape the size distribution of observed infection clusters. Infection source data for smallpox suggests that primary cases transmitted more than secondary cases, and provides a quantitative assessment of the effectiveness of control interventions. Human monkeypox, on the other hand, does not show evidence of differential transmission between animals in contact with humans, primary cases, or secondary cases, which assuages the concern that social mixing can amplify transmission by secondary cases. Lastly, we evaluate surveillance requirements for detecting a change in the human-to-human transmission of monkeypox since the cessation of cross-protective smallpox vaccination. Our studies lay the foundation for future investigations regarding how infection source, vaccination status or other putative transmissibility traits may affect self-limited transmission.

No MeSH data available.


Related in: MedlinePlus