scholarly journals Decision letter: Using parasite genetic and human mobility data to infer local and cross-border malaria connectivity in Southern Africa

2019 ◽  
Author(s):  
Samir Bhatt ◽  
Thomas S Churcher
2019 ◽  
Author(s):  
Sofonias Tessema ◽  
Amy Wesolowski ◽  
Anna Chen ◽  
Maxwell Murphy ◽  
Jordan Wilheim ◽  
...  

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Sofonias Tessema ◽  
Amy Wesolowski ◽  
Anna Chen ◽  
Maxwell Murphy ◽  
Jordan Wilheim ◽  
...  

Local and cross-border importation remain major challenges to malaria elimination and are difficult to measure using traditional surveillance data. To address this challenge, we systematically collected parasite genetic data and travel history from thousands of malaria cases across northeastern Namibia and estimated human mobility from mobile phone data. We observed strong fine-scale spatial structure in local parasite populations, providing positive evidence that the majority of cases were due to local transmission. This result was largely consistent with estimates from mobile phone and travel history data. However, genetic data identified more detailed and extensive evidence of parasite connectivity over hundreds of kilometers than the other data, within Namibia and across the Angolan and Zambian borders. Our results provide a framework for incorporating genetic data into malaria surveillance and provide evidence that both strengthening of local interventions and regional coordination are likely necessary to eliminate malaria in this region of Southern Africa.


2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Nicholas J. Arisco ◽  
Cassio Peterka ◽  
Marcia C. Castro

Abstract Background Cross-border malaria is a major barrier to elimination efforts. Along the Venezuela-Brazil-Guyana border, intense human mobility fueled primarily by a humanitarian crisis and illegal gold mining activities has increased the occurrence of cross-border cases in Brazil. Roraima, a Brazilian state situated between Venezuela and Guyana, bears the greatest burden. This study analyses the current cross-border malaria epidemiology in Northern Brazil between the years 2007 and 2018. Methods De-identified data on reported malaria cases in Brazil were obtained from the Malaria Epidemiological Surveillance Information System for the years 2007 to 2018. Pearson’s Chi-Square test of differences was utilized to assess differences between characteristics of cross-border cases originating from Venezuela and Guyana, and between border and transnational cases. A logistic regression model was used to predict imported status of cases. Results Cross-border cases from Venezuela and Guyana made up the majority of border and transnational cases since 2012, and Roraima remained the largest receiving state for cross-border cases over this period. There were significant differences in the profiles of border and transnational cases originating from Venezuela and Guyana, including type of movement and nationality of patients. Logistic regression results demonstrated Venezuelan and Guyanese nationals, Brazilian miners, males, and individuals of working age had heightened odds of being an imported case. Furthermore, Venezuelan citizens had heightened odds of seeking care in municipalities adjacent Venezuela, rather than transnational municipalities. Conclusions Cross-border malaria contributes to the malaria burden at the Venezuela-Guyana-Brazil border. The identification of distinct profiles of case importation provides evidence on the need to strengthen surveillance at border areas, and to deploy tailored strategies that recognize different mobility routes, such as the movement of refuge-seeking individuals and of Brazilians working in mining.


2015 ◽  
Author(s):  
Sally Peberdy ◽  
Jonathan Crush ◽  
Daniel Tevera ◽  
Eugene Campbell ◽  
Ines Raimundo ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shaobin Wang ◽  
Yun Tong ◽  
Yupeng Fan ◽  
Haimeng Liu ◽  
Jun Wu ◽  
...  

AbstractSince spring 2020, the human world seems to be exceptionally silent due to mobility reduction caused by the COVID-19 pandemic. To better measure the real-time decline of human mobility and changes in socio-economic activities in a timely manner, we constructed a silent index (SI) based on Google’s mobility data. We systematically investigated the relations between SI, new COVID-19 cases, government policy, and the level of economic development. Results showed a drastic impact of the COVID-19 pandemic on increasing SI. The impact of COVID-19 on human mobility varied significantly by country and place. Bi-directional dynamic relationships between SI and the new COVID-19 cases were detected, with a lagging period of one to two weeks. The travel restriction and social policies could immediately affect SI in one week; however, could not effectively sustain in the long run. SI may reflect the disturbing impact of disasters or catastrophic events on the activities related to the global or national economy. Underdeveloped countries are more affected by the COVID-19 pandemic.


Author(s):  
Shuhei Nomura ◽  
Yuta Tanoue ◽  
Daisuke Yoneoka ◽  
Stuart Gilmour ◽  
Takayuki Kawashima ◽  
...  

AbstractIn the COVID-19 era, movement restrictions are crucial to slow virus transmission and have been implemented in most parts of the world, including Japan. To find new insights on human mobility and movement restrictions encouraged (but not forced) by the emergency declaration in Japan, we analyzed mobility data at 35 major stations and downtown areas in Japan—each defined as an area overlaid by several 125-meter grids—from September 1, 2019 to March 19, 2021. Data on the total number of unique individuals per hour passing through each area were obtained from Yahoo Japan Corporation (i.e., more than 13,500 data points for each area). We examined the temporal trend in the ratio of the rolling seven-day daily average of the total population to a baseline on January 16, 2020, by ten-year age groups in five time frames. We demonstrated that the degree and trend of mobility decline after the declaration of a state of emergency varies across age groups and even at the subregional level. We demonstrated that monitoring dynamic geographic and temporal mobility information stratified by detailed population characteristics can help guide not only exit strategies from an ongoing emergency declaration, but also initial response strategies before the next possible resurgence. Combining such detailed data with data on vaccination coverage and COVID-19 incidence (including the status of the health care delivery system) can help governments and local authorities develop community-specific mobility restriction policies. This could include strengthening incentives to stay home and raising awareness of cognitive errors that weaken people's resolve to refrain from nonessential movement.


2021 ◽  
Vol 10 (2) ◽  
pp. 73
Author(s):  
Raquel Pérez-Arnal ◽  
David Conesa ◽  
Sergio Alvarez-Napagao ◽  
Toyotaro Suzumura ◽  
Martí Català ◽  
...  

The COVID-19 pandemic is changing the world in unprecedented and unpredictable ways. Human mobility, being the greatest facilitator for the spread of the virus, is at the epicenter of this change. In order to study mobility under COVID-19, to evaluate the efficiency of mobility restriction policies, and to facilitate a better response to future crisis, we need to understand all possible mobility data sources at our disposal. Our work studies private mobility sources, gathered from mobile-phones and released by large technological companies. These data are of special interest because, unlike most public sources, it is focused on individuals rather than on transportation means. Furthermore, the sample of society they cover is large and representative. On the other hand, these data are not directly accessible for anonymity reasons. Thus, properly interpreting its patterns demands caution. Aware of that, we explore the behavior and inter-relations of private sources of mobility data in the context of Spain. This country represents a good experimental setting due to both its large and fast pandemic peak and its implementation of a sustained, generalized lockdown. Our work illustrates how a direct and naive comparison between sources can be misleading, as certain days (e.g., Sundays) exhibit a directly adverse behavior. After understanding their particularities, we find them to be partially correlated and, what is more important, complementary under a proper interpretation. Finally, we confirm that mobile-data can be used to evaluate the efficiency of implemented policies, detect changes in mobility trends, and provide insights into what new normality means in Spain.


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