Public health policies to contain the spread of COVID-19 rely mainly on non-pharmacological measures. Those measures, especially social distancing, are a challenge for developing countries, such as Brazil. In São Paulo, the most populous state in Brazil (45 million inhabitants), most COVID-19 cases up to April 18th were reported in the Capital and metropolitan area. However, the inner municipalities, where 20 million people live, are also at risk. As governmental authorities discuss the loosening of measures for restricting population mobility, it is urgent to analyze the routes of dispersion of COVID-19 in São Paulo territory. We hypothesize that urban hierarchy is the main responsible for the disease spreading, and we identify the hotspots and the main routes of virus movement from the metropolis to the inner state. In this ecological study, we use geographic models of population mobility to check for patterns for the spread of SARS-CoV-2 infection. We identify two patterns based on surveillance data: one by contiguous diffusion from the capital metropolitan area, and the other hierarchical with long-distance spread through major highways that connects São Paulo city with cities of regional relevance. This knowledge can provide real-time responses to support public health strategies, optimizing the use of resources in order to minimize disease impact on population and economy.
RESUMO Para compreender como a Covid-19 se distribui pelo espaço brasileiro, os geógrafos utilizam-se do raciocínio geográfico apoiados em técnicas de mapeamento e representações espaciais. Nesse sentido, propomos aqui uma série de procedimentos para compreender a doença no espaço, primeiramente com a exploração e descrição dos dados, a análise espacial e a síntese por meio da modelização gráfica, partindo em seguida para a comunicação cartográfica. Como efeito, esperamos que esse caminho teórico e metodológico possa balizar a criação de uma imagem de mundo capaz de responder a demandas mais urgentes postas pela pandemia, ao mesmo tempo criar reflexões sobre como a produção do espaço atual cria vulnerabilidades nesta globalização perversa.
Two hundred days after the first confirmed case of COVID-19 in Brazil, the epidemic has rapidly spread in metropolitan areas and advanced throughout the countryside. We followed the temporal epidemic pattern at São Paulo State, the most populous of the country, the first to have a confirmed case of COVID-19, and the one with the most significant number of cases until now. We analysed the number of new cases per day in each regional health department and calculated the effective reproduction number (Rt) over time. Social distance measures, along with improvement in testing and isolating positive cases, general population mask-wearing and standard health security protocols for essential and non-essential activities, were adopted and impacted on slowing down epidemic velocity but were insufficient to stop transmission.
Usability issues of maps presented in-car Route Guidance and Navigation System (RGNS) may result in serious impacts on traffic safety. To obtain effective RGNS, evaluation of 'user satisfaction' with the system has played a prominent role, since designers can quantify drivers' acceptance about presented information. An important variable related to design of RGNS interfaces refers to select appropriate scale for maps, since it interferes on legibility of maps. Map with good legibility may support drivers comprehend information easily and take decisions during driving task quickly. This paper evaluates drivers' preference for scales used in maps of RGNS. A total of 52 subjects participated of an experiment performed in a parked car. Maps were designed at four different scales 1:1,000, 1:3,000, 1:6,000 and 1:10,000 for a route composed of 13 junctions. Map design was based on cartographic communication principles, such as perceptive grouping and figure-ground segregation. Based on studies cases, we conclude intermediate scales (1:6,000 and 1:3,000) were more acceptable among drivers compared to large scales (1:1,000) and small (1:10,000). RGNS should select scales for maps which supports drivers to quickly identify direction of the maneuver and, simultaneously, get information about surroundings of route. More results are presented and implications discussed
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