Dataset Information

Leveraging a Bayesian network approach to model and analyze supplier vulnerability to severe weather risk: A case study of the U.S. pharmaceutical supply chain following Hurricane Maria.

ABSTRACT: The United States government has identified the health care sector as part of the critical infrastructure for homeland security to protect citizens against health risks arising from terrorism, natural disasters, and epidemics. Citizens also have expectations about the role that health care plays in enjoying a good quality of life, by providing response systems to handle emergencies and other illness situations adequately. Among the systems required to supportdesired performance levels is a robust and resilient pharmaceutical supply chain that is free of disruption. Shortages of drugs place undue pressure on healthcare providers to devise alternative approaches to administer patient care. With climate change expected to result in increasingly severe weather patterns in the future, it is critical that logistics engineers understand the impact that a catastrophic weather event could have on supply chain disruption to facilitate the design of supply systems that are robust and resilient. This study investigates the main causal and intermediate events that led to risk propagation in, and disruption of, the U.S. pharmaceutical supply chain following Hurricane Maria. A causality Bayesian model is developed to depict linkages between risk events and quantify the associated cumulative risk. The quantification is further examined through different advanced techniques such as predictive inference reasoning and sensitivity analysis. The general interpretation of these analyses suggests that port resilience is imperative to pharmaceutical supply chain performance in the case of Puerto Rico.

SUBMITTER: Lawrence JM

PROVIDER: S-EPMC7187851 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Leveraging a Bayesian network approach to model and analyze supplier vulnerability to severe weather risk: A case study of the U.S. pharmaceutical supply chain following Hurricane Maria.

Lawrence Jeanne-Marie JM Ibne Hossain Niamat Ullah NU Jaradat Raed R Hamilton Michael M

International journal of disaster risk reduction : IJDRR 20200428

The United States government has identified the health care sector as part of the critical infrastructure for homeland security to protect citizens against health risks arising from terrorism, natural disasters, and epidemics. Citizens also have expectations about the role that health care plays in enjoying a good quality of life, by providing response systems to handle emergencies and other illness situations adequately. Among the systems required to supportdesired performance levels is a robus ...[more]

PMID: 32346504

Similar Datasets

Project description:ImportanceAs public health emergencies become more prevalent, it is crucial to identify adverse physical and mental health conditions that may be triggered by natural disasters. There is a lack of data on whether Hurricane Maria in 2017 influenced the disease burden of adults in Puerto Rico.ObjectiveTo estimate the prevalence of chronic diseases and their associated risk factors among adults living in Puerto Rico before and after Hurricane Maria in 2017.Design, setting, and participantsThis cross-sectional study used data from 2 previous cross-sectional studies, including the pre-Hurricane Maria Puerto Rico Assessment on Diet, Lifestyles and Disease (PRADLAD) study, conducted in 2015, and the post-Hurricane Maria Puerto Rico Observational Study of Psychosocial, Environmental, and Chronic Disease Trends (PROSPECT), conducted in 2019. Participants included adults aged 30 to 75 years residing in Puerto Rico. Data were analyzed from April to October 2020.ExposuresSelf-reported data were obtained on sociodemographic, lifestyle, and psychosocial factors and medically diagnosed conditions using validated questionnaires. Anthropometrics were measured in triplicate.Main outcomes and measuresData were obtained using similar protocols in both studies. Characteristics were contrasted for all participants across studies and for 87 PRADLAD participants who returned to PROSPECT.ResultsA total of 825 participants from both cohorts were included, with 380 PRADLAD participants and 532 PROSPECT participants. In the 2019 PROSPECT study, the mean (SD) age was 53.7 (10.8) years, and 363 participants (68.2%) were assigned female at birth and 169 participants (31.8%) were assigned male at birth. In the 2019 cohort, 360 participants (67.7%) had college education or higher, 205 participants (38.5%) reported annual income greater than $20 001, and 263 participants (49.5%) were employed. Most sociodemographic variables were similar between studies, except for higher income and employment after the hurricane. In the main analysis, participants in 2019, compared with participants in 2015, had higher abdominal obesity (389 participants [73.2%] vs 233 participants [61.3%]), sedentarism (236 participants [44.4%] vs 136 participants [35.8%]), binge drinking (95 participants [17.9%] vs 46 participants [12.1%]), and social support (mean [SD] score, 26.9 [7.2] vs 24.7 [7.1]) but lower depressive symptoms (169 participants [31.7%] vs 200 participants [52.6%]) and perceived stress (mean [SD] score, 19.3 [9.5] vs 21.7 [7.7]). In 2019, compared with 2015, there were higher rates of hypertension (252 participants [47.3%] vs 149 participants [39.2%]), arthritis (172 participants [32.3%] vs 97 participants [25.6%]), high cholesterol (194 participants [36.4%] vs 90 participants [23.8%]), high triglycerides (123 participants [23.1%] vs 56 participants [14.7%]), eye disease (94 participants [17.6%] vs 48 participants [12.7%]), fatty liver disease (68 participants [12.8%] vs 29 participants [7.5%]), and osteoporosis (74 participants [13.9%] vs 20 participants [5.2%]). Secondary analysis for the 87 returning participants showed similar results.Conclusions and relevanceIn this cross-sectional study, a higher prevalence of unhealthy behaviors and chronic conditions was noted among adults in Puerto Rico after Hurricane Maria, warranting long-term studies. Psychosocial factors were better, but still need attention. As natural disasters intensify, efforts should focus on continuous surveillance of health outcomes and promoting healthy behaviors, positive emotional health, and disease control, particularly in populations with higher risk for poor health.

Dataset Information

Leveraging a Bayesian network approach to model and analyze supplier vulnerability to severe weather risk: A case study of the U.S. pharmaceutical supply chain following Hurricane Maria.

Publications

Leveraging a Bayesian network approach to model and analyze supplier vulnerability to severe weather risk: A case study of the U.S. pharmaceutical supply chain following Hurricane Maria.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets