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Assessing the mandatory bovine abortion notification system in France using unilist capture-recapture approach.

ABSTRACT: The mandatory bovine abortion notification system in France aims to detect as soon as possible any resurgence of bovine brucellosis. However, under-reporting seems to be a major limitation of this system. We used a unilist capture-recapture approach to assess the sensitivity, i.e. the proportion of farmers who reported at least one abortion among those who detected such events, and representativeness of the system during 2006-2011. We implemented a zero-inflated Poisson model to estimate the proportion of farmers who detected at least one abortion, and among them, the proportion of farmers not reporting. We also applied a hurdle model to evaluate the effect of factors influencing the notification process. We found that the overall surveillance sensitivity was about 34%, and was higher in beef than dairy cattle farms. The observed increase in the proportion of notifying farmers from 2007 to 2009 resulted from an increase in the surveillance sensitivity in 2007/2008 and an increase in the proportion of farmers who detected at least one abortion in 2008/2009. These patterns suggest a raise in farmers' awareness in 2007/2008 when the Bluetongue Virus (BTV) was detected in France, followed by an increase in the number of abortions in 2008/2009 as BTV spread across the country. Our study indicated a lack of sensitivity of the mandatory bovine abortion notification system, raising concerns about the ability to detect brucellosis outbreaks early. With the increasing need to survey the zoonotic Rift Valley Fever and Q fever diseases that may also cause bovine abortions, our approach is of primary interest for animal health stakeholders to develop information programs to increase abortion notifications. Our framework combining hurdle and ZIP models may also be applied to estimate the completeness of other clinical surveillance systems.

SUBMITTER: Bronner A

PROVIDER: S-EPMC3653928 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundEpidemiology of Neisseria meningitidis has been changing since the introduction of universal vaccination programmes against meningococcal serogroup C (MenC) and meningococcal serogroup B (MenB) has now become dominant. This study aimed to analyse the cases reported in institutional data recording systems to estimate the burden of invasive meningococcal diseases (IMDs) and assess the effectiveness of surveillance in Veneto region (Italy).MethodsAnalysis was performed from 2007 to 2014 on data recorded in different systems: Mandatory Notification System, National Surveillance of Invasive Bacterial Diseases System and Laboratories Surveillance System (LSS), which were pooled into a combined surveillance system (CSS) and hospital discharge records (HDRs). A capture-recapture method was used and completeness of each source estimated. Number of cases with IMD by source of information and year, incidence of IMD by age group, case fatality rate (CFR) and distribution of meningococcal serogroups by year were also analysed.ResultsCombining the four data systems enabled the identification of 179 confirmed cases with IMD, achieving an overall sensitivity of 94.7% (95% CI: 90.8% to 98.8%), while it was 76.7% (95% CI: 73.6% to 80.1%) for CSS and 77.2% (95% CI: 74.1% to 80.6%) for HDRs. Typing of isolates was done in 80% of cases, and 95.2% of the typed cases were provided by LSS. Serogroup B was confirmed in 50.3% of cases. The estimated IMD notification rate (cases with IMD diagnosed and reported to the surveillance systems) was 0.48/100 000 population, and incidence peaked at 6.2/100 000 in children aged <1?year old (60.9% due to MenB), and increased slightly in the age group between 15 and 19 years (1.1/100 000). A CFR of 14% was recorded (8.7% in paediatric age).ConclusionsQuality of surveillance systems relies on case ascertainment based on serological characterisation of the circulating strains by microbiology laboratories. All available sources should be routinely combined to improve the epidemiology of IMD and the information used by public health departments to conduct timely preventive measures.

Project description:IntroductionDigital exposure notification (EN) approaches may offer considerable advantages over traditional contact tracing in speed, scale, efficacy, and confidentiality in pandemic control. We applied the science of learning health systems to test the effect of framing and digital means, email vs Short Message Service (SMS), on EN adoption among patients of an academic health center.MethodsWe tested three communication approaches of the Apple and Google EN system in a rapid learning cycle involving 15 000 patients pseudorandomly assigned to three groups. The patients in the first group received a 284-word email that presented EN as a tool that can help slow the spread. The patients in the second group received a 32-word SMS that described EN as a new tool to help slow the spread (SlowTheSpreadSMS). Patients in the third group received a 47-word SMS that depicted the system as a new digital tool that can empower them to protect their family and friends (EmpowerSMS). A brief four-question anonymous survey of adoption was included in a reminder message sent 2 days after the initial outreach.ResultsOne hundred and sixty people responded to the survey within 1 week: 2.33% from EmpowerSMS, 0.97% from SlowTheSpreadSMS, and 0.53% from emails; 29 (41.43%), 24 (41.38%), and 11 (34.38%) reported having adopted EN from each group, respectively. Patient reported barriers to adoption included iOS version incompatibility, privacy concerns, and low trust of government agencies or companies like Apple and Google. Patients recommended that healthcare systems play an active role in disseminating information about this tool. Patients also recommended advertising on social media and providing reassurance about privacy.ConclusionsThe EmpowerSMS resulted in relatively more survey responses. Both SMS groups had slightly higher, but not statistically significant EN adoption rates compared to email. Findings from the pilot not only informed operational decision-making in our health system but also contributed to EN rollout planning in our State.

Project description:Few studies have evaluated the optimal sampling design for tracking small mammal population trends, especially for rare or difficult to detect species. Spatially explicit capture-recapture (SECR) models present an advancement over non-spatial models by accounting for individual movement when estimating density. The salt marsh harvest mouse (SMHM; Reithrodontomys raviventris) is a federal and California state listed endangered species endemic to the San Francisco Bay-Delta estuary, California, USA; where a population in a subembayment has been continually monitored over an 18-year period using mark-recapture methods. We analyzed capture data within a SECR modeling framework that allowed us to account for differences in detection and movement between sexes. We compared the full dataset to subsampling scenarios to evaluate how the grid size (area) of the trap design, trap density (spacing), and number of consecutive trapping occasions (duration) influenced density estimates. To validate the subsampling methods, we ran Monte Carlo simulations based on the true parameter estimates for each specific year. We found that reducing the area of the trapping design by more than 36% resulted in the inability of the SECR model to replicate density estimates within the SE of the original density estimates. However, when trapping occasions were reduced from 4 to 3-nights the density estimates were indistinguishable from the full dataset. Furthermore, reducing trap density by 50% also resulted in density estimates comparable to the full dataset and was a substantially better model than reducing the trap area by 50%. Overall, our results indicated that moderate reductions in the number of trapping occasions or trap density could yield similar density estimates when using a SECR approach. This approach allows the optimization of field trapping efforts and designs by reducing field efforts while maintaining the same population estimate compared to the full dataset. Using a SECR approach may help other wildlife programs identify sampling efficiencies without sacrificing data integrity for long term monitoring of population densities.

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Assessing the mandatory bovine abortion notification system in France using unilist capture-recapture approach.

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