Research Projects

1. Understanding Polydrug Use Pattern Among Opioid Use Disorder (OUD) Patients Using Healthcare Claim Data

--> Understanding Polydrug use pattern using unsupervised data mining techniques

The USA is facing an unprecedented opioid epidemic that costs more than 72,000 lives in the US so far from 1999 to 2017 [11]. The US population consume almost 80% prescription opioids drugs in the world while OUD diagnosis grew to 493% over a seven-year period, from 2010 to 2016. Though many population studies are looking at both behavioral and drug usage aspects among OUD patients, but Polydrug use have not investigated thoroughly yet. In reality, an OUD patient is addicted to more than one drugs and Polydrug use also has been shown to be associated with non-fatal and fatal drug overdose. In my research, I am developing unsupervised data mining methods to understand the hidden Polydurg use pattern among OUD patients where I am using data from Connecticut and Rhode Island states. I am using association rule mining and complexity science to develop this new tool.

Main aims of this project is are to understand

a. How Polydrug use changes both temporally and spatially within and between states

b. How illicit drugs change the drug user patterns

This project is using open source drug overdoses data and OPTUM Clinfomratics data. This project provides key determinants of Polydrug use among OUD users.

2. Agent-based Modeling of Infections Diseases

Transmission dynamics of enteric diseases

--> Identifying the relationships of age, number of previous infections and rotavirus-associated gastroenteritis (RVGE) using statistical modeling

Rotavirus infection is the most common cause of severe diarrhea among children under 5 years of age in both developing and developed regions of the world. The introduction tow live oral rotavirus vaccine in 81 countries as of May 2016 has been a major public health success in the last decade and has led to substantial reductions in hospitalization and rotavirus-associated gastroenteritis (RVGE) morbidity. However, the vaccines are performing better in developed world while struggling in developing counties. There are many hypotheses exist in defining the low performance which include oral polio vaccine co-administration, poor nutrition, ,environmental enteric dysfunction individual susceptibility and poor sanitation. We reanalyzed two birth-cohort studies to identify whether age and number of previous infection can be good predictor of any RVGE and moderate -to-severe RVGE using generalized linear framework.

--> Developing an individual-based modeling framework to quantify different transmission heterogeneities of rotavirus

We are developing an individual-based model (IBM) of rotavirus transmission dynamics in developing country settings. The IBM model will be fitted to the birth cohort data and will be using to predict the vaccine efficacy for different settings to quantify the setting specific parameters.

Modeling mycobacterial transmission dynamics in agricultural systems

-->Individual Based Modeling of Mycobacterium Avium Subsp. Paratuberculosis(MAP)

The objective of this project is to develop an hybrid individual based model, which will simultaneously take data from the field and whole genome sequencing analysis of different MAP strains results. An individual based model has already been developed which provides the individual information values over MAP infection dynamics in an endemic herd. Normally, Johne’s disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP) infection, results in economic losses in dairy industry. In the United States, the cost to dairy producers due to the impact of Johne’s disease on milk production was estimated to be more than $200 million per year.Johne’s disease prevalence has been increasing and is currently one of the more important infectious diseases in cattle. Prevalence of MAP infection (the proportion of detected animals shedding low and high quantities of MAP within a herd)is generally low, but control of Johne’s disease is difficult due to the long incubation period and low test sensitivities for animals shedding low quantities of MAP. To lower the risk of MAP infection and reduce potential economic loss, producers have frequently applied test-based culling of infectious animals in herds as a control measure. More about our individual-based model will be found in the following articles

A flow diagram of infection categories for the adult animals in the herd. Each category (boxes) classifies animals according to their initial setup. The probabilities of exit at each time point from susceptible to latent, latent to low shedding and low shedding to high shedding animals are s1, h1, and y1, respectively. Vertical transmission probabilities from latent, low shedders and high shedders animals are Vh,Vy1, and Vy2, respectively. Horizontal transmission probabilities to calves from low shedders and high shedders animals are Hy1 and Hy2, respectively. The probability a calf is infected by colostrum/milk from infected animals is β m . Calf-to-calf and heifer-to-heifer transmission probabilities are C inf and Y inf , respectively. Stochastic death/sale probabilities for adult, calves, and heifers are µa, µc, and µh, respectively.

References

1. Al-Mamun, M.A., Grohn, Y.T., Smith, R.L., & Schukken, Y.T., 2017. Use of an individual-based model to control transmission pathways of Mycobacterium Avium Sups. paratuberculosis infection in cattle herds. Scientific Reports 7(1):11845.

2. Al-Mamun, M.A., Smith, R.L., and Schukken, Y., & Grohn, Y.T., (2016). Modeling of Mycobacterium Avium Subsp. Paratuberculosis Dynamics in a Dairy Herd: An Individual Based Approach. Journal of Theoretical Biology, 408, pp.105-117.

3. Al-Mamun, M.A., and Gröhn, Y.T., 2017. MABSDairy: A multiscale agent-based simulation of a dairy herd, in ANSS '17 Proceedings of the 50th Annual Simulation Symposium, Spring Simulation Multi-Conference, Virginia Beach, Virginia -April 23 - 26, 2017.

Funding: US-UK collab: mycobacterial transmission dynamics in agricultural systems: integrating phylogenetics, epidemiology, ecology, and economics. USDA, USDA-NIFA-Award no: 72159

-->Modeling of Economic Consequences of Johne’s disease in Dairy Herd

This study presents the economic analysis of different intervention/culling strategies in case of US dairy herd point of view. More specifically, this study considers several key factors as constraints for maintaining a good intervention strategies. More reading resources can be found in following articles

References

1 .Chiu, L.V., Tauer, L.W., Al-Mamun, M.A., Kaniyamattam, K., Smith, R.l., & Grohn, Y.T., 2018. An agent-based model evaluation of economic control strategies for paratuberculosis in a dairy herd, Journal of Dairy Science.

2. Smith, R.L., Al-Mamun, M.A., & Gröhn, Y.T. (2017). Economic consequences of paratuberculosis control in dairy cattle: a stochastic modeling study. Preventive Veterinary Medicine, 138, pp.17-27.

Funding: US-UK collab: mycobacterial transmission dynamics in agricultural systems: integrating phylogenetics, epidemiology, ecology, and economics. USDA, USDA-NIFA-Award no: 72159