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System Dynamics Helps Evaluate Anticipatory Action on Cholera Outbreaks

Jul 3, 2024 | Cases, Health Policy, Water

EXECUTIVE Summary

  • Cholera remains a significant public health problem in the Democratic Republic of the Congo (DRC), with 13,000 suspected cases and 236 deaths reported in 2022 alone. In light of these complexities and volatilities, it is crucial for humanitarian response to move from a largely reactive to an anticipatory approach according to the Centre for Humanitarian Data.

  • The System Dynamics model plays a substantial role in the learning process of the anticipatory action pilot project, by simulating various scenarios involving different anticipatory actions. The case-area targeted intervention (CATI) approach involves the early detection of primary outbreak cases and delivery of a rapid response to households around the case’s household to substantially reduce transmission via synergistic interventions that act in the short term (i.e. point-of-use water treatment, hygiene promotion with soap distribution, and antibiotic chemoprophylaxis).

  • Depending on the timing and the capacity of the anticipatory activities, the model findings demonstrate positive outcomes from early interventions, with up to 40% of deaths potentially avoided. Moreover, the findings highlight the critical role of anticipatory approach in buying more time for vaccination efforts.

#Cholera #DisasterResponse #Outbreak #DRC

The Problem

The Democratic Republic of Congo (DRC) is grappling with one of the world’s most complex and prolonged humanitarian crises, suffering from mass population displacement, acute food insecurity, severe malnutrition, epidemics, and protection issues. Cholera is endemic, particularly in the conflict-ridden eastern provinces, which accounted for 89% of the country’s cases and 62% of its deaths in 2022. Furthermore, outbreaks also occur in non-endemic areas. The situation is complicated by administrative and logistical challenges, the isolation of some regions, and a deteriorating security situation, making humanitarian responses exceptionally difficult.

Despite a decrease in cholera cases since 2019, the fatality rate has increased, and the Ministry of Health reports a rise in cases in 2022. There is a convergence of points of view of international humanitarian aid, according to which there must me a move from a largely reactive to an anticipatory approach. This involves planning for the occurrence of a next disaster: setting up an action plan and securing funding before the disaster hits, disburse funds to reduce an outbreak impact, and, therefore, mitigate humanitarian needs.

The Solution

Today, the occurrence and the impact of humanitarian interventions on different crisis can be projected with high confidence. Evidence indicates that proactive action before a foreseeable threat materialises is more effective than traditional reactive humanitarian responses. The System Dynamics model of Yemen Cholera Response modeled by Loo, Anaely, and Kopainsky (2022) explores the implications of the joint interventions with different start times and demonstrates that 40% of deaths could potentially have been prevented if the same interventions had been initiated earlier in April 2017, in Al-Hudaydah, Yemen.

Anticipatory action aims to trigger the release of funds much earlier than is currently the case, in order to respond quickly when cases are detected. Humanitarian agencies encourage collective learning based on the impact from the anticipatory action pilot project in the DRC. By adapting the Yemen Cholera Response model to the DRC context and simulating various anticipatory action scenarios, the System Dynamics model plays a substantial role in the learning process of the anticipatory action pilot project.

The high-level stock and flow diagram illustrates an extended Susceptible, Infectious, and Recovered (SIR) model that integrates the cholera outbreak response’s operational dynamics featuring targeted interventions in water, sanitation, hygiene, data surveillance, and health sectors. The anticipatory action framework prioritises enhancing early detection and curbing the transmission of cholera by mobilising rapid response from the CATI teams. These teams work in homes with suspected cases, distributing water, sanitation and hygiene (WASH) kits, sharing hygiene information, disinfecting these homes and their surroundings, and bolstering surveillance capacity.

The main feedback loops:

Infection loop (Reinforcing feedback loop): This loop describes how susceptible individuals (S) come into contact with infectious individuals (I), leading to an increase in the number of infections.
Recovery and loss of immunity loop (Balancing feedback loop): In this loop, infected individuals recover (R) and move from the infectious category back to the susceptible category due to the loss of immunity over time.

These feedback loops are essential in understanding the dynamics of disease spread and recovery in a population, as well as intervention leverage points.

Outcomes

The model facilitates understanding the impact of single or combined interventions initiated at varying times. In adapting the Yemen Cholera Response model, two additional interventions – water system and CATI – were incorporated into the System Dynamics model.

The findings from the present model are in line with the findings from the Yemen Cholera Response model where both models highlight the critical roles of an anticipatory approach (or other short-term emergency response interventions) in buying more time for vaccination efforts. The System Dynamics model plays a substantial role in the learning process of the anticipatory action pilot project, by simulating various scenarios involving different anticipatory actions.

More importantly, the implementation of the anticipatory action for cholera in the DRC will help foster scientific findings and the refinement of the cholera simulation model, increasing the model confidence and robustness. The next phase aims to incorporate the findings from monitoring and evaluating implemented activities back into the System Dynamics model, thereby bolstering the model’s robustness.

Figure – User interface used for analysing the impacts of interventions with different capacities, demands, and start times.

Do you want to know more?

Connect with Pei Shan Loo and L Milano.

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Upcoming Events

Pre-College SIG July meeting (Asia-Pacific)

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Dear Colleagues, We would like to invite you to our July System Dynamics Society Pre-College Special Interest Group meeting. We want to discuss a preliminary stock-flow model on the topic of Peer Bullying in K–12. We will have two meetings due to time differences. The...