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More than 1 billion people live in informal settlements worldwide, where precarious living conditions pose unique challenges to managing a COVID-19 outbreak. Taking Northwest Syria as a case study, we simulated an outbreak in high-density informal Internally Displaced Persons (IDP) camps using a stochastic Susceptible-Exposed-Infectious-Recovered model. Expanding on previous studies, taking social conditions and population health/structure into account, we modelled several interventions feasible in these settings: moderate self-distancing, self-isolation of symptomatic cases and protection of the most vulnerable in ‘safety zones’. We considered complementary measures to these interventions that can be implemented autonomously by these communities, such as buffer zones, health checks and carers for isolated individuals, quantifying their impact on the micro-dynamics of disease transmission. All interventions significantly reduce outbreak probability and some of them reduce mortality when an outbreak does occur. Self-distancing reduces mortality by up to 35% if contacts are reduced by 50%. A reduction in mortality by up to 18% can be achieved by providing one self-isolation tent per eight people. Protecting the most vulnerable in a safety zone reduces the outbreak probability in the vulnerable population and has synergistic effects with the other interventions. Our model predicts that a combination of all simulated interventions may reduce mortality by more than 90% and delay an outbreak’s peak by almost 2 months. Our results highlight the potential for non-medical interventions to mitigate the effects of the pandemic. Similar measures may be applicable to controlling COVID-19 in other informal settlements, particularly IDP camps in conflict regions, around the world.

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In the wake of the COVID-19 pandemic, travel restrictions implemented to prevent its spread, likethe suspension of international transit and closure of borders, first put into place in March 2020, oftensuddenly, have created complex, fast-evolving networks of restrictions between the countries of origin anddestination of migrants and would-be migrants. These restrictions have had a particularly noteworthyimpact on migrants from North and West Africa, who have reported experiencing greater impacts from thepandemic on their journeys than migrants from any other region in the world, as flows registered throughkey transit points in West and Central Africa and irregular arrivals to Europe plummeted, especiallyalong the Western Mediterranean Route key to migrants from North and West Africa. The InternationalOrganization for Migration (IOM) has postulated that international migrant stocks have fallen well shortof their pre-pandemic projections in West/North Africa, Europe, and globally, by more than 2 million,due to travel restrictions. However, this is not testable with migration data from traditional sourceslike censuses and population surveys, which on top of pre-existing timeliness and granularity limitations,have had data collection operations delayed, canceled, interrupted, or data quality otherwise seriouslycompromised by the pandemic. Recognizing these challenges, key migration stakeholders, including theIOM, have called for the use of data from alternative sources, including social media, to fill in thesegaps. Inspired by this call, we endeavor to test the hypothesis that COVID-related travel restrictionsreduced migrant stock compared to what it would have been in the absence of such restrictions usingestimates of expats, or individuals living in a given destination country who formerly lived in a givenorigin country, from Facebook’s advertising platform. We take advantage of the quasi-natural experimentprovided by different countries’ staggered adoption of different levels of travel restrictions, which weformulate as a treatment, and attempt to control for non-travel restriction-related factors that may besimultaneously influencing migration, using the method developed by Arellano and Bond for estimatingdynamic linear panel models. Looking specifically at four key origin countries in North and West Africa,Côte d’Ivoire, Algeria, Morocco, and Senegal, and their 23 key destination countries, we estimate thata destination country implementing a total entry ban over the course of a month may have expected a3.39% reduction in migrant stock compared to the counterfactual in which no travel restrictions wereimplemented. However, when taking pandemic-related mortality, broader restrictions on activity andmovement, and the onset of the global pandemic itself into account, we estimate that a destinationcountry implementing an entry ban over the course of a month may expect a 5.47% increase in migrantstock. While further research is needed on both the impact of the COVID-19 pandemic on migrationand using social media data to obtain accurate migration estimates, travel restrictions do not appear tohave been effective in curbing migration in the countries that implement them in the context of the widerdisruptions wrought by the pandemic.

Domestic military installations generate high levels of noise due to testing and training which leads to annoyance and complaints from surrounding communities. This necessitates continuous noise monitoring to provide decision makers with the information they need to proactively manage their noise environment. Due to the diverse climates in which military testing and training are conducted (e.g., desert, tundra, and rainforest), monitoring equipment that can operate in a variety of environmental conditions with minimal maintenance and low power consumption is needed. Using existing technologies as a baseline, various iterations of a low-cost acoustic monitor were designed to meet these constraints while minimizing initial investment cost, improving the mean time between failures, and increasing overall system capability. This paper will describe the system developed to provide a rapid deployment option that is robust to extreme temperatures, humidity, and destructive wildlife. A review of operational logs collected during multiple deployments was used to evaluate system performance against benchtop and off-the-shelf solutions. This data demonstrate the reliability of the monitoring stations and the sustainability of their hardware.

This paper describes a method for non-coplanar microphone arrays that temporally isolates and cleans unknown broadband acoustic impulses for detection, classification, and scene analysis. Possible events are initially identified using a sliding statistical time window. Then the authors posit that most of the false triggers due to environmental noise can be filtered by using generalized cross correlation to phase align the microphone channels and reject implausible velocities. Finally, the phase aligned signals are calibrated and averaged across the microphones. With appropriate hyperparameter tuning, this method appears robust to ambient noise, wind noise and physical interaction. Performance is measured using a simulation and a real historic dataset of over 2 hours of curated acoustic recordings containing 559 gunshots, 120 blasts, and 747 other various weather and non-impulsive events recorded with no prior information under normal operating conditions. Events were found and validated using human listeners with a tool to visualize the waveform and the spectrogram. For this dataset, the model accurately found over 95% of the gunshots with 92% temporal separation and 100% of the blasts identified by the listeners. These results show the method to be a viable solution for impulsive outdoor broadband acoustic signal detection.

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.