Evidence map›Paper›PMID 27500957›Full record

ArticlePLoS neglected tropical diseases2016

Human Rabies in China, 1960-2014: A Descriptive Epidemiological Study.

Hang Zhou, Sirenda Vong, Kai Liu, Yu Li, Di Mu, Liping Wang, Wenwu Yin, Hongjie Yu

Open access · goldAbstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
4.3field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.

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  15. You AreAnimals : an open access journal from MDPI · 2023
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  18. A Descriptive Analysis of Human Rabies in Mainland China, 2005-2020.International journal of environmental research and public health · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Hang ZhouDivision of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Sirenda VongWorld Health Organization, China Office, Beijing, China.
Kai LiuDivision of Infectious Diseases, Xiaogan Center for Disease Control and prevention, Xiaogan City, China.
Yu LiDivision of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Di MuDivision of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Liping WangDivision of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Wenwu YinDivision of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Hongjie YuDivision of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Chinese Center For Disease Control and Prevention · CNFudan University · CN

Funding

Virology &ImmunologyU19AI051915 · NIAID · NATIONAL CENTER FOR AIDS/STD CONTROL AND PREVENTION · PI SHAO, YIMING · 2002 to 2009
$21.6M
NIAID NIH HHS U19 AI051915World Health Organization 001
6 · The paper itself

Abstract

backgroundRabies in China remains a public health problem. In 2014, nearly one thousand rabies-related deaths were reported while rabies geographic distribution has expanded for the recent years. This report used surveillance data to describe the epidemiological characteristics of human rabies in China including determining high-risk areas and seasonality to support national rabies prevention and control activities.

methodsWe analyzed the incidence and distribution of human rabies cases in mainland China using notifiable surveillance data from 1960-2014, which includes a detailed analysis of the recent years from 2004 to 2014.

resultsFrom 1960 to 2014, 120,913 human rabies cases were reported in mainland China. The highest number was recorded in 1981(0.7/100,000; 7037 cases), and in 2007(0.3/100,000; 3300 cases). A clear seasonal pattern has been observed with a peak in August (11.0% of total cases), Human rabies cases were reported in all provinces with a yearly average of 2198 from 1960 to 2014 in China, while the east and south regions were more seriously affected compared with other regions. From2004 to 2014, although the number of cases decreased by 65.2% since 2004 from 2651 to 924 cases, reported areas has paradoxically expanded from 162 prefectures to 200 prefectures and from southern to the central and northern provinces of China. Farmers accounted most of the cases (65.0%); 50-59 age group accounted for the highest proportion (20.5%), and cases are predominantly males with a male-to-female ratio of 2.4:1 on average.

conclusionsDespite the overall steady decline of cases since the peak in 2007, the occurrence of cases in new areas and the spread trend were obvious in China in recent years. Further investigations and efforts are warranted in the areas have high rabies incidence to control rabies by interrupting transmission from dogs to humans and in the dog population. Furthermore, elimination of rabies should be eventually the ultimate goal for China.

Indexed as

AdolescentAdultAgedAnimalsChildChild, PreschoolChinaDemographyDogsEpidemiologic StudiesFemaleGeographyHumansIncidenceInfantInfant, Newborn

Identifiers

PMID27500957
PMCPMC4976867
OpenAlexW2505063554

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.