| Literature DB >> 22709741 |
Luke Mondor1, John S Brownstein, Emily Chan, Lawrence C Madoff, Marjorie P Pollack, David L Buckeridge, Timothy F Brewer.
Abstract
To compare the timeliness of nongovernmental and governmental communications of infectious disease outbreaks and evaluate trends for each over time, we investigated the time elapsed from the beginning of an outbreak to public reporting of the event. We found that governmental sources improved the timeliness of public reporting of infectious disease outbreaks during the study period.Entities:
Mesh:
Year: 2012 PMID: 22709741 PMCID: PMC3376818 DOI: 10.3201/eid1807.120249
Source DB: PubMed Journal: Emerg Infect Dis ISSN: 1080-6040 Impact factor: 6.883
Time from the estimated start of an outbreak to its earliest communication by source*
| Variable | Governmental sources | Nongovernmental sources | p value | |||
|---|---|---|---|---|---|---|
| No. outbreaks | Median no. days (95% CI) | No. outbreaks | Median no. days (95% CI) | |||
| Period | ||||||
| 1996–2009 | 163 | 33.0 (30–44) | 103 | 23.0 (20–32) | 0.200 | |
| Pre-SARS | 90 | 39.5 (31–51) | 61 | 29.0 (20–50) | 0.161 | |
| Post-SARS | 73 | 29.0 (25–37) | 42 | 21.5 (17–32) | 0.613 | |
| Geographic location | ||||||
| Africa | 85 | 37.0 (29–51) | 41 | 31.0 (23–57) | 0.733 | |
| Americas | 13 | 30.0 (21–63) | 12 | 25.0 (20–34) | 0.568 | |
| Eastern Mediterranean | 24 | 41.0 (23–51) | 9 | 31.0 (16–82) | 0.903 | |
| Europe | 11 | 31.0 (23–79) | 9 | 20.0 (13–184) | 0.909 | |
| Southeast Asia | 8 | 28.0 (10–62) | 11 | 14.0 (11–51) | 0.431 | |
| Western Pacific | 22 | 26.0 (12–52) | 21 | 18.0 (13–33) | 0.789 | |
*Bootstrapping with 10,000 replicates was used to calculate 95% CIs for median values. SARS, severe acute respiratory syndrome.
Figure 1Exclusion criteria applied to database of 398 outbreak events publicly reported through the World Health Organization (WHO) Disease Outbreak News during 1996–2009 and breakdown of nongovernmental and governmental sources used to compare the timeliness of outbreak communications. UN, United Nations. *More than one source may be identified for a given outbreak; †categories for exclusion are not mutually exclusive; ‡health officials, ministries of health, laboratories, hospitals, etc.; §included in sensitivity analysis; ¶includes nongovernmental organizations, individual accounts, ProMED requests for information, and multiple sources.
Comparison of the timeliness of outbreak communications by nongovernmental and governmental sources*
| Variable | IRR (95% CI) | p value |
|---|---|---|
| Source | ||
| Governmental | Ref | |
| Nongovernmental | 0.950 (0.765–1.180) | 0.645 |
| Chronological order | ||
| Pre-SARS | Ref | |
| Post-SARS | 0.713 (0.576–0.884) | 0.002 |
| Geographic location | ||
| Africa | Ref | |
| Americas | 0.773 (0.531–1.126) | 0.180 |
| Eastern Mediterranean | 0.912 (0.654–1.272) | 0.587 |
| Europe | 1.100 (0.731–1.669) | 0.637 |
| Southeast Asia | 0.602 (0.394–0.918) | 0.019 |
| Western Pacific | 0.780 (0.577–1.054) | 0.106 |
*Methods: The multivariate negative binomial regression model compared the timeliness of outbreaks first communicated by nongovernmental sources to those by governmental sources, while adjusting for geographic region and whether the outbreak occurred before or after public recognition of SARS. IRR, incidence rate ratio; SARS, severe acute respiratory syndrome; ref, reference value = 1. Reference categories: (1) source: governmental, (2) SARS: pre-SARS, (3) geographic region: Africa.
Figure 2Median time (days) from the estimated start of an outbreak to its public communication for outbreaks reported by nongovernmental sources (A) and governmental sources (B), 1996–2009. Trendlines show average improvements over the study period.