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一种估算国际交通对疟疾病例影响的模型:以日本为例,时间范围为 1999 年至 2021 年。

A Model to Estimate the Effect of International Traffic on Malaria Cases: The Case of Japan from 1999 to 2021.

机构信息

Public Health, Department of Social Medicine, Graduate School of Medicine, Osaka University, Osaka 565-0871, Japan.

Cabinet Secretariat, Tokyo 100-8968, Japan.

出版信息

Int J Environ Res Public Health. 2022 Jan 13;19(2):880. doi: 10.3390/ijerph19020880.

Abstract

Aiming to identify the potentially reduced malaria cases by stagnation of international traffic after the COVID-19 pandemic, a longitudinal analysis of malaria cases as well as entries of Japanese and foreigners was conducted using data from 5 April 1999 to 30 September 2021 in Japan. Multivariable risk ratios were calculated with the Poison regression model as a predictive model of malaria cases by the number of entries for Japanese and foreigners. A generalized regression model was used to examine an association of time trend with entries for Japanese and foreigners using data before 2019, to estimate the potentially reduced number of entries after 2020. The potentially reduced number of malaria cases was estimated by the potentially reduced number of entries for Japanese and foreigners after 2020 using a multivariable Poison regression model. The multivariable risk ratio (95% confidence intervals) of malaria case numbers per 100,000 persons increment of entries per day was 3.41 (1.50-7.77) for Japanese and 1.47 (0.92-2.35) for foreigners. During 2020, a potential reduction of 28 (95% confidence limit: 22-34) malaria cases was estimated, which accounted for 58% (52-63%) of malaria cases in Japan. These finding suggest that the stagnation of international traffic during the COVID-19 pandemic reduced the number of malaria cases in Japan. This model may be helpful for countries without indigenous malaria to predict future trends of imported malaria cases.

摘要

为了确定 COVID-19 大流行后国际交通停滞可能导致的疟疾病例减少,对 1999 年 4 月 5 日至 2021 年 9 月 30 日期间日本的疟疾病例以及日本人和外国人入境数据进行了纵向分析。使用泊松回归模型作为预测模型,计算了日本人和外国人入境人数与疟疾病例数的多变量风险比。使用广义回归模型,根据 2019 年之前的数据,考察了时间趋势与日本人及外国人入境的关系,以估计 2020 年后入境人数减少的潜在数量。使用多变量泊松回归模型,根据 2020 年后日本人和外国人入境人数减少的潜在数量,估计疟疾病例减少的潜在数量。日本人每天入境人数每增加 100,000 人疟疾病例数的多变量风险比(95%置信区间)为 3.41(1.50-7.77),外国人的风险比为 1.47(0.92-2.35)。2020 年,预计将减少 28 例(95%置信限:22-34)疟疾病例,占日本疟疾病例的 58%(52-63%)。这些发现表明,COVID-19 大流行期间国际交通的停滞减少了日本的疟疾病例数量。该模型可能有助于没有本土疟疾的国家预测未来输入性疟疾病例的趋势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8fb7/8775555/943cc8bf7979/ijerph-19-00880-g001.jpg

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