Empowering the crowd: Feasible strategies for epidemic management in high-density informal settlements. The case of COVID-19 in Northwest Syria

Abstract

More than 1 billion people live in informal settlements worldwide, where precarious living conditions pose additional challenges to the management of a COVID-19 outbreak. Well-established measures, such as social distancing, testing, contact tracing, improved hygiene, and generalized use of personal protective equipment, are almost impossible to implement. We specifically investigated the impact of adapting these measures to informal settlements located in regions immersed in protracted conflicts, taking the Northwest region of Syria (NWS) as a case study. Such regions need to contend with the public health challenges resulting from violence, deterioration of health-systems, and political instability. We implemented a stochastic Susceptible-Exposed-Infectious-Recovered model to simulate the spread of the virus in high-density camps of Internally Displaced Persons, using a population structure representative of these camps. We chose parameters corresponding to a worst-case scenario where there is no healthcare available. We expanded on previous models to adapt feasible interventions to the living conditions in the camps, including moderate self-distancing, self-isolation of symptomatic individuals, and protection of the most vulnerable in "safety zones". All the interventions significantly reduce the probability of observing an outbreak and the death toll. Self-distancing brings the best results if contacts are reduced by 50%, with mortality reduced by up to 35%. A similar reduction in mortality can be achieved by providing 1 self-isolation tent per 200 individuals. Protecting the vulnerable in a safety zone has synergistic effects with previous interventions for the whole population, but is especially beneficial for the vulnerable population. Complementary measures, such as lockdown of the safety zone when a first case is detected in the camp, further reduce mortality and the probability of an outbreak. Our model predicts that a combination of all simulated interventions may reduce mortality by as much as 80%. The time until the number of symptomatic cases peaks is delayed by most of the interventions, in some cases by more than three months. The proportion of the population that recovers, near 70%, could help prevent future outbreaks. Our results highlight the potential of non-medical interventions to mitigate the effects of the pandemic. They demonstrate that interventions shown to be effective in other settings can be adapted to refugee camps and are most effective when implemented in tandem. Our modelization considers complementary measures to these interventions that can be implemented autonomously by these communities, such as buffer zones, daily health-checks, and carers for isolated individuals, quantifying their impact on the micro-dynamics of disease transmission. Similar measures may be applicable to controlling COVID-19 in other informal settlements, particularly Internally Displaced Persons camps in conflict regions, around the world.