Modeling Optimal Laboratory Testing Strategies for Bacterial Meningitis Surveillance in Africa.
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ABSTRACT:
SUBMITTER: Walker J
PROVIDER: S-EPMC8409536 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:As economic woes of the COVID-19 pandemic deepen, strategies are being formulated to avoid the need for prolonged stay-at-home orders, while implementing risk-based quarantine, testing, contact tracing and surveillance protocols. Given limited resources and the significant economic, public health, and operational challenges of the current 14-day quarantine recommendation, it is vital to understand if shorter but equally effective quarantine and testing strategies can be deployed. To quantify the probability of post-quarantine transmission upon isolation of a positive test, we developed a mathematical model in which we varied quarantine duration and the timing of molecular tests for three scenarios of entry into quarantine. Specifically, we consider travel quarantine, quarantine of traced contacts with an unknown time if infection, and quarantine of cases with a known time of exposure. With a one-day delay between test and result, we found that testing on exit (or entry and exit) can reduce the duration of a 14-day quarantine by 50%, while testing on entry shortened quarantine by at most one day. Testing on exit more effectively reduces post-quarantine transmission than testing upon entry. Furthermore, we identified the optimal testing date within quarantines of varying duration, finding that testing on exit was most effective for quarantines lasting up to seven days. As a real-world validation of these principles, we analyzed the results of 4,040 SARS CoV-2 RT-PCR tests administered to offshore oil rig employees. Among the 47 positives obtained with a testing on entry and exit strategy, 16 cases that previously tested negative at entry were identified, with no further cases detected among employees following quarantine exit. Moreover, this strategy successfully prevented an expected nine offshore transmission events stemming from cases who had tested negative on the entry test, each one a serious concern for initiating rapid spread and a disabling outbreak in the close quarters of an offshore rig. This successful outcome highlights that appropriately timed testing can make shorter quarantines more effective, thereby minimizing economic impacts, disruptions to operational integrity, and COVID-related public health risks.
| S-EPMC7654919 | biostudies-literature
Project description:For COVID-19, it is vital to understand if quarantines shorter than 14 days can be equally effective with judiciously deployed testing. Here, we develop a mathematical model that quantifies the probability of post-quarantine transmission incorporating testing into travel quarantine, quarantine of traced contacts with an unknown time of infection, and quarantine of cases with a known time of exposure. We find that testing on exit (or entry and exit) can reduce the duration of a 14-day quarantine by 50%, while testing on entry shortens quarantine by at most one day. In a real-world test of our theory applied to offshore oil rig employees, 47 positives were obtained with testing on entry and exit to quarantine, of which 16 had tested negative at entry; preventing an expected nine offshore transmission events that each could have led to outbreaks. We show that appropriately timed testing can make shorter quarantines effective.
| S-EPMC7788536 | biostudies-literature
Project description:Meningococcal meningitis remains a significant public health threat, especially in the African meningitis belt where Neisseria meningitidis serogroup A historically caused large-scale epidemics. With the rollout of a novel meningococcal serogroup A conjugate vaccine (MACV) in the belt, the World Health Organization recommended case-based meningitis surveillance to monitor MACV impact and meningitis epidemiology. In 2014, the MenAfriNet consortium was established to support strategic implementation of case-based meningitis surveillance in 5 key countries: Burkina Faso, Chad, Mali, Niger, and Togo. MenAfriNet aimed to develop a high-quality surveillance network using standardized laboratory and data collection protocols, develop sustainable systems for data management and analysis to monitor MACV impact, and leverage the surveillance platform to perform special studies. We describe the MenAfriNet consortium, its history, strategy, implementation, accomplishments, and challenges.
| S-EPMC6853281 | biostudies-literature
Project description:Although many African countries have achieved high levels of HIV diagnosis, funding constraints have necessitated greater focus on more efficient testing approaches. We compared the impact and cost-effectiveness of several potential new testing strategies in South Africa, and assessed the prospects of achieving the UNAIDS target of 95% of HIV-positive adults diagnosed by 2030. We developed a mathematical model to evaluate the potential impact of home-based testing, mobile testing, assisted partner notification, testing in schools and workplaces, and testing of female sex workers (FSWs), men who have sex with men (MSM), family planning clinic attenders and partners of pregnant women. In the absence of new testing strategies, the diagnosed fraction is expected to increase from 90.6% in 2020 to 93.8% by 2030. Home-based testing combined with self-testing would have the greatest impact, increasing the fraction diagnosed to 96.5% by 2030, and would be highly cost-effective compared to currently funded HIV interventions, with a cost per life year saved (LYS) of $394. Testing in FSWs and assisted partner notification would be cost-saving; the cost per LYS would also be low in the case of testing MSM ($20/LYS) and self-testing by partners of pregnant women ($130/LYS).
| S-EPMC6718403 | biostudies-literature
Project description:BackgroundThis study aims to assess the most efficient combinations of vaccination and screening coverage for the prevention of cervical cancer (CC) at different levels of expenditure in Nigeria.MethodsAn optimization procedure, using a linear programming approach and requiring the use of two models (an evaluation and an optimization model), was developed. The evaluation model, a Markov model, estimated the annual number of CC cases at steady state in a population of 100,000 women for four alternative strategies: screening only; vaccination only; screening and vaccination; and no prevention. The results of the Markov model for each scenario were used as inputs to the optimization model determining the optimal proportion of the population to receive screening and/or vaccination under different scenarios. The scenarios varied by available budget, maximum screening and vaccination coverage, and overall reachable population.ResultsIn the base-case optimization model analyses, with a coverage constraint of 20% for one lifetime screening, 95% for vaccination and a budget constraint of $1 per woman per year to minimize CC incidence, the optimal mix of prevention strategies would result in a reduction of CC incidence of 31% (3-dose vaccination available) or 46% (2-dose vaccination available) compared with CC incidence pre-vaccination. With a 3-dose vaccination schedule, the optimal combination of the different strategies across the population would be 20% screening alone, 39% vaccination alone and 41% with no prevention, while with a 2-dose vaccination schedule the optimal combination would be 71% vaccination alone, and 29% with no prevention. Sensitivity analyses indicated that the results are sensitive to the constraints included in the optimization model as well as the cervical intraepithelial neoplasia (CIN) and CC treatment cost.ConclusionsThe results of the optimization model indicate that, in Nigeria, the most efficient allocation of a limited budget would be to invest in both vaccination and screening with a 3-dose vaccination schedule, and in vaccination alone before implementing a screening program with a 2-dose vaccination schedule.
| S-EPMC4057561 | biostudies-literature
Project description:Since early March 2020, government agencies have utilized a wide variety of non-pharmaceutical interventions to mitigate the spread of COVID-19 and have struggled to determine when it is appropriate to return to in-person activities after an outbreak is detected. At many universities, fundamental issues related to understanding the spread of the disease (e.g. the transmission rate), the ability of administrators to respond quickly enough by closing when there is a sudden rise in cases, and how to make a decision on when to reopen remains a concern. Surveillance testing strategies have been implemented in some places, and those test outcomes have dictated whether to reopen, to simultaneously monitor community spread, and/or to isolate discovered cases. However, the question remains as to when it is safe to reopen and how much testing is required to remain safely open while keeping infection numbers low. Here, we propose an extension of the classic SIR model to investigate reopening strategies for a fixed testing strategy, based on feedback from testing results. Specifically, we close when a predefined proportion of the population becomes infected, and later reopen when that infected proportion decreases below a predefined threshold. A valuable outcome of our approach is that our reopening strategies are robust to variation in almost all model parameters, including transmission rates, which can be extremely difficult to determine as they typically differ between variants, location, vaccination status, etc. Thus, these strategies can be, in theory, translated over to new variants in different regions of the world. Examples of robust feedback strategies for high disease transmission and a fixed testing capacity include (1) a single long lock down followed by a single long in-person period, and (2) multiple shorter lock downs followed by multiple shorter in-person periods. The utility of this approach of having multiple strategies is that administrators of universities, schools, business, etc. can use a strategy that is best adapted for their own functionality.
| S-EPMC9645599 | biostudies-literature
Project description:BACKGROUND:The MenAfriNet Consortium supports strategic implementation of case-based meningitis surveillance in key high-risk countries of the African meningitis belt: Burkina Faso, Chad, Mali, Niger, and Togo. We describe bacterial meningitis epidemiology in these 5 countries in 2015-2017. METHODS:Case-based meningitis surveillance collects case-level demographic and clinical information and cerebrospinal fluid (CSF) laboratory results. Neisseria meningitidis, Streptococcus pneumoniae, or Haemophilus influenzae cases were confirmed and N. meningitidis/H. influenzae were serogrouped/serotyped by real-time polymerase chain reaction, culture, or latex agglutination. We calculated annual incidence in participating districts in each country in cases/100 000 population. RESULTS:From 2015-2017, 18 262 suspected meningitis cases were reported; 92% had a CSF specimen available, of which 26% were confirmed as N. meningitidis (n = 2433; 56%), S. pneumoniae (n = 1758; 40%), or H. influenzae (n = 180; 4%). Average annual incidences for N. meningitidis, S. pneumoniae, and H. influenzae, respectively, were 7.5, 2.5, and 0.3. N. meningitidis incidence was 1.5 in Burkina Faso, 2.7 in Chad, 0.4 in Mali, 14.7 in Niger, and 12.5 in Togo. Several outbreaks occurred: NmC in Niger in 2015-2017, NmC in Mali in 2016, and NmW in Togo in 2016-2017. Of N. meningitidis cases, 53% were NmC, 30% NmW, and 13% NmX. Five NmA cases were reported (Burkina Faso, 2015). NmX increased from 0.6% of N. meningitidis cases in 2015 to 27% in 2017. CONCLUSIONS:Although bacterial meningitis epidemiology varied widely by country, NmC and NmW caused several outbreaks, NmX increased although was not associated with outbreaks, and overall NmA incidence remained low. An effective low-cost multivalent meningococcal conjugate vaccine could help further control meningococcal meningitis in the region.
| S-EPMC6853282 | biostudies-literature
Project description:BackgroundThe introduction of MenAfriVac in campaigns targeting people aged 1-29 years across the African meningitis belt has successfully reduced meningitis incidence and carriage due to Neisseria meningitidis group A (MenA). It is important to consider how best to sustain population protection in the long term.MethodsWe created a mathematical model of MenA transmission and disease to investigate the potential impact of a range of immunization strategies. The model is age structured; includes classes of susceptible, carrier, ill, and immune people (who may be vaccinated or unvaccinated); and incorporates seasonal transmission and a stochastic forcing term that models between year variation in rates of transmission. Model parameters were primarily derived from African sources. The model can describe the typical annual incidence of meningitis in the prevaccine era, with irregular epidemics of varying size. Parameter and structural uncertainty were explored in sensitivity analyses.ResultsFollowing MenAfriVac introduction at high uptake, the model predicts excellent short-term disease control. With no subsequent immunization, strong resurgences in disease incidence were predicted after approximately 15 years (assuming 10 years' average vaccine protection). Routine immunization at 9 months of age resulted in lower average annual incidence than regular mass campaigns of 1- to 4-year-olds, provided coverage was above approximately 60%. The strategy with the lowest overall average annual incidence and longest time to resurgence was achieved using a combination strategy of introduction into the Expanded Programme on Immunization at 9 months, 5 years after the initial mass campaigns, with a catch-up targeting unvaccinated 1- to 4-year-olds.ConclusionsThese results can be used to inform policy recommendations for long-term vaccination strategies with MenAfriVac.
| S-EPMC4639487 | biostudies-literature
Project description:IntroductionThe Risk Identification Unit (RIU) of the US Dept. of Agriculture's Center for Epidemiology and Animal Health (CEAH) conducts weekly surveillance of national livestock health data and routine coordination with agricultural stakeholders. As part of an initiative to increase the number of species, health issues, and data sources monitored, CEAH epidemiologists are building a surveillance system based on weekly syndromic counts of laboratory test orders in consultation with Colorado State University laboratorians and statistical analysts from the Johns Hopkins University Applied Physics Laboratory. Initial efforts focused on 12 years of equine test records from three state labs. Trial syndrome groups were formed based on RIU experience and published literature. Exploratory analysis, stakeholder input, and laboratory workflow details were needed to modify these groups and filter the corresponding data to eliminate alerting bias. Customized statistical detection methods were sought for effective monitoring based on specialized laboratory information characteristics and on the likely presentation and animal health significance of diseases associated with each syndrome.MethodsData transformation and syndrome formation focused on test battery type, test name, submitter source organization, and specimen type. We analyzed time series of weekly counts of tests included in candidate syndrome groups and conducted an iterative process of data analysis and veterinary consultation for syndrome refinement and record filters. This process produced a rule set in which records were directly classified into syndromes using only test name when possible, and otherwise, the specimen type or related body system was used with test name to determine the syndrome. Test orders associated with government regulatory programs, veterinary teaching hospital testing protocols, or research projects, rather than clinical concerns, were excluded. We constructed a testbed for sets of 1000 statistical trials and applied a stochastic injection process assuming lognormally distributed incubation periods to choose an alerting algorithm with the syndrome-required sensitivity and an alert rate within the specified acceptable range for each resulting syndrome. Alerting performance of the EARS C3 algorithm traditionally used by CEAH was compared to modified C2, CuSUM, and EWMA methods, with and without outlier removal and adjustments for the total weekly number of non-mandatory tests.ResultsThe equine syndrome groups adopted for monitoring were abortion/reproductive, diarrhea/GI, necropsy, neurological, respiratory, systemic fungal, and tickborne. Data scales, seasonality, and variance differed widely among the weekly time series. Removal of mandatory and regulatory tests reduced weekly observed counts significantly-by >80% for diarrhea/GI syndrome. The RIU group studied outcomes associated with each syndrome and called for detection of single-week signals for most syndromes with expected false-alert intervals >8 and <52 weeks, 8-week signals for neurological and tickborne monitoring (requiring enhanced sensitivity), 6-week signals for respiratory, and 4-week signals for systemic fungal. From the test-bed trials, recommended methods, settings and thresholds were derived.ConclusionsUnderstanding of laboratory submission sources, laboratory workflow, and of syndrome-related outcomes are crucial to form syndrome groups for routine monitoring without artifactual alerting. Choices of methods, parameters, and thresholds varied by syndrome and depended strongly on veterinary epidemiologist-specified performance requirements.
| S-EPMC6396905 | biostudies-literature
Project description:This study aimed to assess whether surveillance intensity is associated with recurrence and survival in colorectal cancer (CRC) patients. Overall, 3794 patients with pathologic stage I-III CRC who underwent radical surgery between January 2012 and December 2014 were examined. Surveillance comprised abdominopelvic computed tomography (CT) every 6 months and chest CT annually for 5 years. Patients who underwent more than and less than an average of three imaging examinations annually were assigned to the high-intensity (HI) and low-intensity (LI) groups, respectively. Demographics were similar in both groups. T and N stages were higher and perineural and lymphovascular invasion were more frequent in the HI group (p < 0.001 each). The mean overall survival (OS) was similar for both groups; however, recurrence-free survival (RFS) was longer (p < 0.001) and post-recurrence survival (PRS) was shorter (p = 0.024) in the LI group. In the multivariate analysis, surveillance intensity was associated with RFS (p < 0.001) in contrast to PRS (p = 0.731). In patients with high recurrence risk predicted using the nomogram, OS was longer in the HI group (p < 0.001). A higher imaging frequency in patients at high risk of recurrence could be expected to lead to a slight increase in PRS but does not improve OS. Therefore, rather than increasing the number of CT scans in high-risk patients, other imaging modalities or innovative approaches, such as liquid biopsy, are required.
| S-EPMC8306168 | biostudies-literature