Evidence map›Paper›PMID 30068318›Full record

ArticleBMC public health2018

Estimating dengue incidence and hospitalization in Malaysia, 2001 to 2013.

Yuan Liang Woon, Chee Peng Hor, Keng Yee Lee, Siti Fatimah Zahra Mohd Anuar, Rose Nani Mudin, Mohd Khadzir Sheikh Ahmad, Suhaya Komari, Faridah Amin, Rahman Jamal, Wei Seng Chen and 4 more

Abstract read
In one paragraph

Article in BMC public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Dengue Seroprevalence and Factors Associated with Dengue Seropositivity in Petaling District, Malaysia.International journal of environmental research and public health · 2022
    Article
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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

14 authors.

Yuan Liang WoonClinical Research Centre, Ministry of Health Malaysia, c/o Third Floor, Dermatology Block, Hospital Kuala Lumpur, Jalan Pahang, 50586, Kuala Lumpur, Malaysia.ORCID 0000-0003-4834-9175
Chee Peng HorKepala Batas Hospital, Ministry of Health Malaysia, Jalan Bertam 2, 13200 Kepala Batas, Penang, Malaysia.
Keng Yee LeeClinical Research Centre, Ministry of Health Malaysia, c/o Third Floor, Dermatology Block, Hospital Kuala Lumpur, Jalan Pahang, 50586, Kuala Lumpur, Malaysia.
Siti Fatimah Zahra Mohd AnuarClinical Research Centre, Ministry of Health Malaysia, c/o Third Floor, Dermatology Block, Hospital Kuala Lumpur, Jalan Pahang, 50586, Kuala Lumpur, Malaysia.
Rose Nani MudinSector of Vector-Borne Disease, Disease Control Division, Ministry of Health Malaysia, 62590, Putrajaya, Malaysia.
Mohd Khadzir Sheikh AhmadHealth Informatic Centre, Planning Division, Ministry of Health Malaysia, 62590, Putrajaya, Malaysia.
Suhaya KomariHealth Informatic Centre, Planning Division, Ministry of Health Malaysia, 62590, Putrajaya, Malaysia.
Faridah AminNational Public Health Laboratory, Lot 1853, Kg, Melayu, 47000, Sungai Buloh, Selangor, Malaysia.
Rahman JamalUKM Medical Molecular Biology Institute, UKM Medical Centre, Jalan Yaacob Latiff, Bandar Tun Razak, 56000 Cheras, Kuala Lumpur, Malaysia.
Wei Seng ChenKlinik Alam Medic, 41, Jalan Perdana 3/4, Taman Puchong Perdana, 47100, Puchong, Selangor, Malaysia.
Pik Pin GohClinical Research Centre, Ministry of Health Malaysia, c/o Third Floor, Dermatology Block, Hospital Kuala Lumpur, Jalan Pahang, 50586, Kuala Lumpur, Malaysia.
Lena YeapStats Consulting Pte Ltd, D7-3-1, Block D7, Pusat Perdagangan Dana 1, Jalan PJU 1A/46, PJU 1A, 47301, Petaling Jaya, Selangor, Malaysia.
Zhuo Ren LimStats Consulting Pte Ltd, D7-3-1, Block D7, Pusat Perdagangan Dana 1, Jalan PJU 1A/46, PJU 1A, 47301, Petaling Jaya, Selangor, Malaysia.
Teck Onn LimClinResearch Pte Ltd, D7-3-1, Block D7, Pusat Perdagangan Dana 1, Jalan PJU 1A/46, PJU 1A, 47301, Petaling Jaya, Selangor, Malaysia. limteckonn@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEpidemiologic measures of the dengue burden such as prevalence and incidence are important for policy-making and monitoring the progress of disease control. It is a common practice where epidemiologic and economic research estimate dengue burden based on notification data. However, a basic challenge in estimating the incidence of dengue is that a significant proportion of infected population are asymptomatic. It can be overcome by using mathematical models that relate observed prevalence and mortality to incidence. In this study, we estimate the trend of dengue incidence and hospitalization in Malaysia.

methodsThis study is based entirely on the available secondary data sources on dengue in Malaysia. The age-specific incidence of dengue between 2001 and 2013 was estimated using the prevalence and mortality estimates in an incidence-prevalence-mortality (IPM) model. Data on dengue prevalence were extracted from six sero-surveys conducted in Malaysia between 2001 and 2013; while statistics on dengue notification and Case Fatality Rate were derived from National Dengue Surveillance System. Dengue hospitalization data for the years 2009 to 2013 were extracted from the Health Informatics Centre and the volumes of dengue hospitalization for hospitals with missing data were estimated with Poisson models.

resultsThe dengue incidence in Malaysia varied from 69.9 to 93.4 per 1000 population (pkp) between 2001 and 2013.The temporal trend in incidence rate was decreasing since 2001. It has been reducing at an average rate of 2.57 pkp per year from 2001 to 2013 (p = 0.011). The age-specific incidence of dengue decreased steadily with dengue incidence reaching zero by age > 70 years. Dengue notification rate has remained stable since 2001 and the number of notified cases each year was only a small fraction of the incident cases (0.7 to 2.3%). Similarly, the dengue hospitalization was larger but still a small fraction of the incident cases (3.0 to 5.6%).

conclusionDengue incidence can be estimated with the use of sero-prevalence surveys and mortality data. This study highlights a reducing trend of dengue incidence in Malaysia and demonstrates the discrepancy between true dengue disease burden and cases reported by national surveillance system. Sero-prevalence studies with representative samples should be conducted regularly to allow better estimation of dengue burden in Malaysia.

Indexed as

Models, TheoreticalAdolescentAdultAgedAge DistributionChildChild, PreschoolDengueFemaleHospitalizationHumansIncidenceInfantInfant, NewbornInformation Storage and RetrievalMalaysiaDengueHospitalizationIncidenceMalaysiaNotificationTime trend

Identifiers

PMID30068318
PMCPMC6090758

What OpenQuestion holds

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Registered trials

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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.