[2010 - 2012年在巴西里约热内卢市使用谷歌地图对死亡信息系统中的地理编码数据进行处理]
[Use of Google Maps for geocoding data from the Mortality Information System in Rio de Janeiro municipality, Brazil, 2010-2012].
作者信息
Silveira Ismael Henrique da, Oliveira Beatriz Fátima Alves de, Junger Washington Leite
机构信息
Universidade do Estado do Rio de Janeiro, Instituto de Medicina Social, Rio de Janeiro-RJ, Brasil.
Fundação Instituto Oswaldo Cruz, Escola Nacional de Saúde Pública Sergio Arouca, Rio de Janeiro-RJ, Brasil.
出版信息
Epidemiol Serv Saude. 2017 Oct-Dec;26(4):881-886. doi: 10.5123/S1679-49742017000400018.
OBJECTIVE
to describe the results of the application of a low cost procedure, using free software, for geocoding data from the Mortality Information System (SIM), in the municipality of Rio de Janeiro.
METHODS
descriptive study using Google Maps database for geocoding deaths data recorded at SIM, occurred from 2010 to 2012, in Rio de Janeiro; the study was carried out in three stages, (i) standardization of addresses, (ii) geocoding by Google Maps, and (iii) manual intervention.
RESULTS
from the total of 26,081 addresses submitted to the procedure, 18,646 (71.5%) had exact matches; the remaining 7,435 were submitted to manual intervention, which found 5,250; 70.6% of the addresses were not initially found; a total of 91.6% of the addresses were geocoded.
CONCLUSION
the procedure presented high proportion of automatic matches and, although it demanded much time, manual intervention allowed a considerable reduction of losses.
目的
描述在里约热内卢市应用一种低成本程序（使用免费软件）对死亡率信息系统（SIM）的数据进行地理编码的结果。
方法
采用描述性研究，利用谷歌地图数据库对2010年至2012年在里约热内卢SIM记录的死亡数据进行地理编码；该研究分三个阶段进行，（i）地址标准化，（ii）通过谷歌地图进行地理编码，以及（iii）人工干预。
结果
在提交给该程序的总共26,081个地址中，18,646个（71.5%）有精确匹配；其余7,435个提交给人工干预，其中找到5,250个；70.6%的地址最初未找到；总共91.6%的地址进行了地理编码。
结论
该程序呈现出较高比例的自动匹配，尽管需要大量时间，但人工干预使损失大幅减少。
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