Impact of drug supply chain on the dynamics of infectious diseases

Paul, Siddhartha; Venkateswaran, Jayendran

doi:10.1002/sdr.1592

Cited by 12 publications

(15 citation statements)

References 39 publications

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“…( 2018 ) introduced a model that simultaneously captures the spatial spread of an epidemic and logistics that can be applied to other infectious diseases; they provide tangible policy recommendations for controlling infectious disease outbreaks over large spatial and temporal scales. In an integrated model, Paul and Venkateswaran ( 2018 ) further showed that epidemic data alone do not suffice to estimate actual disease infectivity, such that corresponding medicine supply chain information (delays, number of echelons, ordering policies) is also necessary. Kochan et al.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The epidemiological literature has investigated the effects of individual and combined interventions (for a review, see Dasaklis et al., 2012 ), such as the outcomes of setting up treatment centers and allocating household protective kits during the 2014 Ebola outbreak (Lewnard et al., 2014 ; Merler et al., 2015 ). However, such studies typically assume zero lead times and automatic replenishment, without accounting for supply chain activities and possible delays (Paul & Venkateswaran, 2018 ). They also often focus on single systems (Chang et al., 2017 ), unlike classic system dynamic models that include interactions among multiple subsystems.…”

Section: Introductionmentioning

confidence: 99%

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Collaboration–competition dilemma in flattening the COVID‐19 curve

Oorschot

Wassenhove

Jahre

2023

Production and Operations Management

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Testing for COVID‐19 is a key intervention that supports tracking and isolation to prevent further infections. However, diagnostic tests are a scarce and finite resource, so abundance in one country can quickly lead to shortages in others, creating a competitive landscape. Countries experience peaks in infections at different times, meaning that the need for diagnostic tests also peaks at different moments. This phase lag implies opportunities for a more collaborative approach, although countries might also worry about the risks of future shortages if they help others by reallocating their excess inventory of diagnostic tests. This article features a simulation model that connects three subsystems: COVID‐19 transmission, the diagnostic test supply chain, and public policy interventions aimed at flattening the infection curve. This integrated system approach clarifies that, for public policies, there is a time to be risk‐averse and a time for risk‐taking, reflecting the different phases of the pandemic (contagion vs. recovery) and the dominant dynamic behavior that occurs in these phases (reinforcing vs. balancing). In the contagion phase, policymakers cannot afford to reject extra diagnostic tests and should take what they can get, in line with a competitive mindset. In the recovery phase, policymakers can afford to give away excess inventory to other countries in need (one‐sided collaboration). When a country switches between taking and giving, in a form of two‐sided collaboration, it can flatten the curve, not only for itself but also for others.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Collaboration–competition dilemma in flattening the COVID‐19 curve

Oorschot

Wassenhove

Jahre

2023

Production and Operations Management

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“…Concerning SC activities, some scant details on past epidemic outbreaks can be retrieved. The pandemic situation significantly impacts every type of supply chain, i.e., the drug supply chain [15], and the food supply chain [16]. Fan, Jamison, and Summers [17] discussed the pandemic risk and estimated the possible annual income losses.…”

Section: Literature Review and Theoretical Developmentmentioning

confidence: 99%

“…V * = v xy (15) W * = w xy (16) Step 4: Calculate the strategy selection matrices from the crisp relation matrices.…”

Section: Proposed Modelmentioning

confidence: 99%

Strategies to Manage the Impacts of the COVID-19 Pandemic in the Supply Chain: Implications for Improving Economic and Social Sustainability

et al. 2020

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This paper aims to identify the negative impacts of the COVID-19 outbreak on supply chains and propose strategies to deal with the impacts in the context of the readymade garment (RMG) industry supply chain of an emerging economy: Bangladesh. To achieve the aims, a methodological framework is proposed through a literature review, expert inputs, and a decision-aid tool, namely the grey-based digraph-matrix method. A total of 10 types of negative impacts and 22 strategic measures to tackle the impacts were identified based on the literature review and expert inputs. Then, the grey-based digraph-matrix was applied for modeling the strategic measures based on their influence to deal with the impacts. Findings reveal that the strategies “manufacturing flexibility”, “diversify the source of supply”, and “develop backup suppliers” have significant positive consequences for managing the impacts of the COVID-19 pandemic in the RMG supply chain. The findings help industrial managers recover from supply chain disruptions by identifying and classifying the impacts and strategies required to manage the major supply chain disturbances caused by the COVID-19 pandemic. As a theoretical contribution, this study is one of few initial attempts to evaluate the impacts of the COVID-19 outbreak and the strategies to deal with the impacts in the supply chain context.

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“…() and Gonçalves (2003) considered the supply chain performance of a semiconductor manufacturer when customers’ response to available inventory was also taken into consideration. More recently, researchers have explored the impact of material delays inherent in multi‐echelon supply chains to explain their impact on materials’ commodities markets (Glöser‐Chahoud et al ., ) and epidemics dynamics (Paul and Venkateswaran, ).…”

Section: Literature Reviewmentioning

confidence: 99%

From boom to bust: an operational perspective of demand bubbles

Gonçalves¹

2018

System Dynamics Review

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When demand exceeds supply, retailers hedge against shortages by placing multiple orders with multiple suppliers, exceeding customer demand and leading to excess capacity, excess inventory, low capacity utilization and financial losses. This paper provides a comprehensive causal loop diagram and a formal mathematical model of a subset of supplier-retailer relationships. We obtain closed-form solutions when supplier capacity is fixed, and analyze simulation dynamics when it is variable. Sensitivity analyses provide a deeper understanding of parameters that contribute to demand bubbles and insight on improvement policies. For instance, the ability of the supplier to build capacity quickly can reduce bubble size. The time it takes retailers to perceive and react to supply availability is an important lever in controlling demand bubbles. When retailers learn of shortages with a delay, their reaction is also delayed, which stabilizes the supply chain.While not an experimental study, Barlas and Gunduz (2011) also find that sharing information significantly reduces the bullwhip effect. Their research using system dynamics finds that policies that share demand and forecast information are very effective in reducing order amplification. P. Gonçalves: From Boom to Bust 393

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Impact of drug supply chain on the dynamics of infectious diseases

Cited by 12 publications

References 39 publications

Collaboration–competition dilemma in flattening the COVID‐19 curve

Collaboration–competition dilemma in flattening the COVID‐19 curve

Strategies to Manage the Impacts of the COVID-19 Pandemic in the Supply Chain: Implications for Improving Economic and Social Sustainability

From boom to bust: an operational perspective of demand bubbles

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