Amna Tariq

All Publications

• GrowthPredict: A toolbox and tutorial-based primer for fitting and forecasting growth trajectories using phenomenological growth models. Scientific reports Chowell, G., Bleichrodt, A., Dahal, S., Tariq, A., Roosa, K., Hyman, J. M., Luo, R. 2024; 14 (1): 1630

  Abstract

  Simple dynamic modeling tools can help generate real-time short-term forecasts with quantified uncertainty of the trajectory of diverse growth processes unfolding in nature and society, including disease outbreaks. An easy-to-use and flexible toolbox for this purpose is lacking. This tutorial-based primer introduces and illustrates GrowthPredict, a user-friendly MATLAB toolbox for fitting and forecasting time-series trajectories using phenomenological dynamic growth models based on ordinary differential equations. This toolbox is accessible to a broad audience, including students training in mathematical biology, applied statistics, and infectious disease modeling, as well as researchers and policymakers who need to conduct short-term forecasts in real-time. The models included in the toolbox capture exponential and sub-exponential growth patterns that typically follow a rising pattern followed by a decline phase, a common feature of contagion processes. Models include the 1-parameter exponential growth model and the 2-parameter generalized-growth model, which have proven useful in characterizing and forecasting the ascending phase of epidemic outbreaks. It also includes the 2-parameter Gompertz model, the 3-parameter generalized logistic-growth model, and the 3-parameter Richards model, which have demonstrated competitive performance in forecasting single peak outbreaks. We provide detailed guidance on forecasting time-series trajectories and available software ( https://github.com/gchowell/forecasting_growthmodels ), including the full uncertainty distribution derived through parametric bootstrapping, which is needed to construct prediction intervals and evaluate their accuracy. Functions are available to assess forecasting performance across different models, estimation methods, error structures in the data, and forecasting horizons. The toolbox also includes functions to quantify forecasting performance using metrics that evaluate point and distributional forecasts, including the weighted interval score. This tutorial and toolbox can be broadly applied to characterizing and forecasting time-series data using simple phenomenological growth models. As a contagion process takes off, the tools presented in this tutorial can help create forecasts to guide policy regarding implementing control strategies and assess the impact of interventions. The toolbox functionality is demonstrated through various examples, including a tutorial video, and the examples use publicly available data on the monkeypox (mpox) epidemic in the USA.

  View details for DOI 10.1038/s41598-024-51852-8

  View details for PubMedID 38238407

  View details for PubMedCentralID PMC10796326

• Factors Associated with Chikungunya Infection among Pregnant Women in Grenada, West Indies. The American journal of tropical medicine and hygiene Kiener, M., Cudjoe, N., Evans, R., Mapp-Alexander, V., Tariq, A., Macpherson, C., Noel, T., Gerardin, P., Waechter, R., LaBeaud, A. D. 2023

  Abstract

  Neonates are vulnerable to vector-borne diseases given the potential for mother-to-child congenital transmission. To determine factors associated with chikungunya virus (CHIKV) infection among pregnant women in Grenada, West Indies, a retrospective cohort study enrolled women who were pregnant during the 2014 CHIKV epidemic. In all, 520/688 women (75.5%) were CHIKV IgG positive. Low incomes, use of pit latrines, lack of home window screens, and subjective reporting of frequent mosquito bites were associated with increased risk of CHIKV infection in bivariate analyses. In the multivariate modified Poisson regression model, low income (adjusted relative risk [aRR]: 1.05 [95% CI: 1.01-1.10]) and frequent mosquito bites (aRR: 1.05 [95% CI: 1.01-1.10]) were linked to increased infection risk. In Grenada, markers of low socioeconomic status are associated with CHIKV infection among pregnant women. Given that Grenada will continue to face vector-borne outbreaks, interventions dedicated to improving living conditions of the most disadvantaged will help reduce the incidence of arboviral infections.

  View details for DOI 10.4269/ajtmh.23-0157

  View details for PubMedID 37253436

• A MATLAB toolbox to fit and forecast growth trajectories using phenomenological growth models: Application to epidemic outbreaks. Research square Chowell, G., Bleichrodt, A., Dahal, S., Tariq, A., Roosa, K., Hyman, J. M., Luo, R. 2023

  Abstract

  Simple dynamic modeling tools can be useful for generating real-time short-term forecasts with quantified uncertainty of the trajectory of diverse growth processes unfolding in nature and society, including disease outbreaks. An easy-to-use and flexible toolbox for this purpose is lacking.In this tutorial-based primer, we introduce and illustrate a user-friendly MATLAB toolbox for fitting and forecasting time-series trajectories using phenomenological dynamic growth models based on ordinary differential equations. This toolbox is accessible to various audiences, including students training in time-series forecasting, dynamic growth modeling, parameter estimation, parameter uncertainty and identifiability, model comparison, performance metrics, and forecast evaluation, as well as researchers and policymakers who need to conduct short-term forecasts in real-time. The models included in the toolbox capture exponential and sub-exponential growth patterns that typically follow a rising pattern followed by a decline phase, a common feature of contagion processes. Models include the 2-parameter generalized-growth model, which has proved useful to characterize and forecast the ascending phase of epidemic outbreaks, and the Gompertz model as well as the 3-parameter generalized logistic-growth model and the Richards model, which have demonstrated competitive performance in forecasting single peak outbreaks.The toolbox provides a tutorial for forecasting time-series trajectories that include the full uncertainty distribution, derived through parametric bootstrapping, which is needed to construct prediction intervals and evaluate their accuracy. Functions are available to assess forecasting performance across different models, estimation methods, error structures in the data, and forecasting horizons. The toolbox also includes functions to quantify forecasting performance using metrics that evaluate point and distributional forecasts, including the weighted interval score.We have developed the first comprehensive toolbox to characterize and forecast time-series data using simple phenomenological growth models. As a contagion process takes off, the tools presented in this tutorial can facilitate policymaking to guide the implementation of control strategies and assess the impact of interventions. The toolbox functionality is demonstrated through various examples, including a tutorial video, and is illustrated using weekly data on the monkeypox epidemic in the USA.

  View details for DOI 10.21203/rs.3.rs-2724940/v1

  View details for PubMedID 37034746

  View details for PubMedCentralID PMC10081381