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Engo-Monsen, K.

Publications and source records attributed to Engo-Monsen, K..

2 recordsLinked to original sources

Megacities as drivers of national outbreaks: the role of holiday travel in the spread of infectious diseases

Human mobility connects populations and can lead to large fluctuations in population density, both of which are important drivers of epidemics. Measuring population mobility during infectious disease outbreaks is challenging, but is a particularly important goal in the context of rapidly growing and highly connected urban centers in low and middle income countries, which can act to amplify and spread local epidemics nationally and internationally. Here, we combine estimates of population movement from mobile phone data for over 4 million subscribers in the megacity of Dhaka, Bangladesh, one of the most densely populated cities globally. We combine mobility data with epidemiological data from a household survey, to understand the role of population mobility on the spatial spread of the mosquito-borne virus chikungunya within and outside Dhaka city during a large outbreak in 2017. The peak of the 2017 chikungunya outbreak in Dhaka coincided with the annual Eid holidays, during which large numbers of people traveled from Dhaka to their native region in other parts of the country. We show that regular population fluxes around Dhaka city played a significant role in determining disease risk, and that travel during Eid was crucial to the spread of the infection to the rest of the country. Our results highlight the impact of large-scale population movements, for example during holidays, on the spread of infectious diseases. These dynamics are difficult to capture using traditional approaches, and we compare our results to a standard diffusion model, to highlight the value of real-time data from mobile phones for outbreak analysis, forecasting, and surveillance.

ecology↗

The geography of malaria elimination in Bangladesh: combining data layers to estimate the spatial spread of parasites

Malaria control programs face difficult resource allocation decisions. Of particular concern for countries aiming for malaria elimination, the regular movement of individuals to and from endemic areas undermines local interventions by reintroducing infections and sustaining local transmission. Quantifying this movement of malaria parasites around a country has become a priority for national control programs, but remains methodologically challenging, particularly in areas with highly mobile populations. Here, we combined multiple data sources to measure the geographical spread of malaria parasites, including epidemiological surveillance data, travel surveys, parasite genetic data, and anonymized mobile phone data. We collected parasite genetic barcodes and travel surveys from 2,090 patients residing in 176 unions in southeast Bangladesh. We developed a genetic mixing index to quantify the likelihood of samples being local or imported. We then inferred the direction and intensity of parasite flow between locations using an epidemiological model, and estimated the proportion of imported cases assuming mobility patterns parameterized using the travel survey and mobile phone calling data. Our results show that each data source provided related but different information about the patterns of geographic spread of parasites. We identify a consistent north/south separation of the Chittagong Hill Tracts region in Bangladesh, and found that in addition to imported infections from forested regions, frequent mixing also occurs in low transmission but highly populated areas in the southwest. Thus, unlike risk maps generated from incidence alone, our maps provide evidence that elimination programs must address ongoing movement of parasites around the lower transmission areas in the southwest.

epidemiology↗