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Systematic comparison of epidemic growth patterns using two different estimation approaches.

ABSTRACT: Background: Different estimation approaches are frequently used to calibrate mathematical models to epidemiological data, particularly for analyzing infectious disease outbreaks. Here, we use two common methods to estimate parameters that characterize growth patterns using the generalized growth model (GGM) calibrated to real outbreak datasets.

Materials and methods: Data from 31 outbreaks are used to fit the GGM to the ascending phase of each outbreak and estimate the parameters using both least squares (LSQ) and maximum likelihood estimation (MLE) methods. We utilize parametric bootstrapping to construct confidence intervals for parameter estimates. We compare the results including RMSE, Anscombe residual, and 95% prediction interval coverage. We also evaluate the correlation between the estimates from both methods.

Results: Comparing LSQ and MLE estimates, most outbreaks have similar parameter estimates, RMSE, Anscombe, and 95% prediction interval coverage. Parameter estimates do not differ across methods when the model yields a good fit to the early growth phase. However, for two outbreaks, there are systematic deviations in model fit to the data that explain differences in parameter estimates (e.g., residuals represent random error rather than systematic deviation).

Conclusion: Our findings indicate that utilizing LSQ and MLE methods produce similar results in the context of characterizing epidemic growth patterns with the GGM, provided that the model yields a good fit to the data.

SUBMITTER: Lee Y

PROVIDER: S-EPMC7691176 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Systematic comparison of epidemic growth patterns using two different estimation approaches.

Lee Yiseul Y Roosa Kimberlyn K Chowell Gerardo G

Infectious Disease Modelling 20201024

<h4>Background</h4>Different estimation approaches are frequently used to calibrate mathematical models to epidemiological data, particularly for analyzing infectious disease outbreaks. Here, we use two common methods to estimate parameters that characterize growth patterns using the generalized growth model (GGM) calibrated to real outbreak datasets.<h4>Materials and methods</h4>Data from 31 outbreaks are used to fit the GGM to the ascending phase of each outbreak and estimate the parameters us ...[more]

PMID: 33294744

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Project description:BackgroundSystematic reviews are used widely to guide health care decisions. Several tools have been created to assess systematic review quality. The measurement tool for assessing the methodological quality of systematic reviews known as the AMSTAR tool applies a yes/no score to eleven relevant domains of review methodology. This tool has been reworked so that each domain is scored based on a four point scale, producing R-AMSTAR.Methods and findingsWe aimed to compare the AMSTAR and R-AMSTAR tools in assessing systematic reviews in the field of assisted reproduction for subfertility. All published systematic reviews on assisted reproductive technology, with the latest search for studies taking place from 2007-2011, were considered. Reviews that contained no included studies or considered diagnostic outcomes were excluded. Thirty each of Cochrane and non-Cochrane reviews were randomly selected from a search of relevant databases. Both tools were then applied to all sixty reviews. The results were converted to percentage scores and all reviews graded and ranked based on this. AMSTAR produced a much wider variation in percentage scores and achieved higher inter-rater reliability than R-AMSTAR according to kappa statistics. The average rating for Cochrane reviews was consistent between the two tools (88.3% for R-AMSTAR versus 83.6% for AMSTAR) but inconsistent for non-Cochrane reviews (63.9% R-AMSTAR vs. 38.5% AMSTAR). In comparing the rankings generated between the two tools Cochrane reviews changed an average of 4.2 places, compared to 2.9 for non-Cochrane.ConclusionR-AMSTAR provided greater guidance in the assessment of domains and produced quantitative results. However, there were many problems with the construction of its criteria and AMSTAR was much easier to apply consistently. We recommend that AMSTAR incorporates the findings of this study and produces additional guidance for its application in order to improve its reliability and usefulness.

Project description:Threats to maintaining high population access with effective bed nets persist due to errors in quantification, bed net wear and tear, and inefficiencies in distribution activities. Monitoring bed net coverage is therefore critical, but usually occurs every 2-3 years through expensive, large-scale household surveys. Mobile phone-based survey methodologies are emerging as an alternative to household surveys and can provide rapid estimates of coverage, however, little research on varied sampling approaches has been conducted in sub-Saharan Africa. A nationally and regionally representative cross-sectional mobile phone survey was conducted in early 2021 in Tanzania with focus on bed net ownership and access. Half the target sample was contacted through a random digit dial methodology (n = 3500) and the remaining half was reached through a voluntary opt-in respondent pool (n = 3500). Both sampling approaches used an interactive voice response survey. Standard RBM-MERG bed net indicators and AAPOR call metrics were calculated. In addition, the results of the two sampling approaches were compared. Population access (i.e., the percent of the population that could sleep under a bed net, assuming one bed net per two people) varied from a regionally adjusted low of 48.1% (Katavi) to a high of 65.5% (Dodoma). The adjusted percent of households that had a least one bed net ranged from 54.8% (Pemba) to 75.5% (Dodoma); the adjusted percent of households with at least one bed net per 2 de facto household population ranged from 35.9% (Manyara) to 55.7% (Dodoma). The estimates produced by both sampling approaches were generally similar, differing by only a few percentage points. An analysis of differences between estimates generated from the two sampling approaches showed minimal bias when considering variation across the indicator for households with at least one bed net per two de facto household population. The results generated by this survey show that overall bed net access in the country appears to be lower than target thresholds. The results suggest that bed net distribution is needed in large sections of the country to ensure that coverage levels remain high enough to sustain protection against malaria for the population.

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Systematic comparison of epidemic growth patterns using two different estimation approaches.

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Systematic comparison of epidemic growth patterns using two different estimation approaches.

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