Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods.
Neonatal invasive disease caused by Group B Streptococcus (GBS) is responsible for much acute mortality and long-term morbidity. To guide development of better prevention strategies, including maternal vaccines that protect neonates against GBS, it is necessary to estimate the burden of this conditi...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2021-06-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1009001&type=printable |
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| author | Bronner P Gonçalves Simon R Procter Sam Clifford Artemis Koukounari Proma Paul Alexandra Lewin Mark Jit Joy Lawn |
| author_facet | Bronner P Gonçalves Simon R Procter Sam Clifford Artemis Koukounari Proma Paul Alexandra Lewin Mark Jit Joy Lawn |
| author_sort | Bronner P Gonçalves |
| collection | DOAJ |
| description | Neonatal invasive disease caused by Group B Streptococcus (GBS) is responsible for much acute mortality and long-term morbidity. To guide development of better prevention strategies, including maternal vaccines that protect neonates against GBS, it is necessary to estimate the burden of this condition globally and in different regions. Here, we present a Bayesian model that estimates country-specific invasive GBS (iGBS) disease incidence in children aged 0 to 6 days. The model combines different types of epidemiological data, each of which has its own limitations: GBS colonization prevalence in pregnant women, risk of iGBS disease in children born to GBS-colonized mothers and direct estimates of iGBS disease incidence where available. In our analysis, we present country-specific maternal GBS colonization prevalence after adjustment for GBS detection assay used in epidemiological studies. We then integrate these results with other epidemiological data and estimate country-level incidence of iGBS disease including in countries with no studies that directly estimate incidence. We are able to simultaneously estimate two key epidemiological quantities: the country-specific incidence of early-onset iGBS disease, and the risk of iGBS disease in babies born to GBS-colonized women. Overall, we believe our method will contribute to a more comprehensive quantification of the global burden of this disease, inform cost-effectiveness assessments of potential maternal GBS vaccines and identify key areas where data are necessary. |
| format | Article |
| id | doaj-art-dbefa243120e4297b86297c192e1b694 |
| institution | Kabale University |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2021-06-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-dbefa243120e4297b86297c192e1b6942025-08-20T03:25:16ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-06-01176e100900110.1371/journal.pcbi.1009001Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods.Bronner P GonçalvesSimon R ProcterSam CliffordArtemis KoukounariProma PaulAlexandra LewinMark JitJoy LawnNeonatal invasive disease caused by Group B Streptococcus (GBS) is responsible for much acute mortality and long-term morbidity. To guide development of better prevention strategies, including maternal vaccines that protect neonates against GBS, it is necessary to estimate the burden of this condition globally and in different regions. Here, we present a Bayesian model that estimates country-specific invasive GBS (iGBS) disease incidence in children aged 0 to 6 days. The model combines different types of epidemiological data, each of which has its own limitations: GBS colonization prevalence in pregnant women, risk of iGBS disease in children born to GBS-colonized mothers and direct estimates of iGBS disease incidence where available. In our analysis, we present country-specific maternal GBS colonization prevalence after adjustment for GBS detection assay used in epidemiological studies. We then integrate these results with other epidemiological data and estimate country-level incidence of iGBS disease including in countries with no studies that directly estimate incidence. We are able to simultaneously estimate two key epidemiological quantities: the country-specific incidence of early-onset iGBS disease, and the risk of iGBS disease in babies born to GBS-colonized women. Overall, we believe our method will contribute to a more comprehensive quantification of the global burden of this disease, inform cost-effectiveness assessments of potential maternal GBS vaccines and identify key areas where data are necessary.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1009001&type=printable |
| spellingShingle | Bronner P Gonçalves Simon R Procter Sam Clifford Artemis Koukounari Proma Paul Alexandra Lewin Mark Jit Joy Lawn Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods. PLoS Computational Biology |
| title | Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods. |
| title_full | Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods. |
| title_fullStr | Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods. |
| title_full_unstemmed | Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods. |
| title_short | Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods. |
| title_sort | estimation of country level incidence of early onset invasive group b streptococcus disease in infants using bayesian methods |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1009001&type=printable |
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