Evidence map›Paper›PMID 41571264›Full record

ArticleAsia-Pacific journal of public health

Time Series Forecasting of Measles Incidence in Pakistan, 2014-2024.

Aruba Adnan, Olaf Berke

Abstract read
In one paragraph

Article in Asia-Pacific journal of public health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Aruba AdnanDepartment of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.ORCID 0009-0002-8818-7991
Olaf BerkeDepartment of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.ORCID 0000-0003-3537-0629

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Measles remains endemic in Pakistan despite global vaccine efforts to prevent its transmission. This study sought to identify the patterns of measles cases in Pakistan, understand the reasons for its recurrence, and determine the optimal timing for measles vaccine campaigns in Pakistan to be most effective. As such, a time series analysis of the monthly measles incidence in Pakistan from 2014 to 2024, obtained from World Health Organization's international measles database, was performed to identify temporal patterns in infections. An increasing trend was identified in the monthly measles cases overtime, along with seasonal swings of low occurrences during the summer, with average lows reaching 304 cases, and a rise during the winter months, with average highs reaching 1038 cases. An automated Seasonal Auto-Regressive Integrated Moving Average (SARIMA) model was further applied to forecast the future incidence of measles, which revealed a three-fold increase in measles cases in the next two years, compared with 2023-2024. Low routine vaccine coverage, topped with climate change related migration and subsequent crowding in urban spaces were found to be major contributors to measles transmission in the country. Findings suggest that supplementary vaccination campaigns are essential and if held in August-September, can mitigate the anticipated rise in measles transmission beginning October every year.

Indexed as

MeaslesForecastingHumansIncidenceMeasles VaccinePakistanSeasonsMeasles Vaccinedisease surveillanceforecastingmeaslesPakistanpublic healthSARIMAtime series analysis

Identifiers

PMID41571264
PMCPMC13039220

What OpenQuestion holds

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LicenceCC BY-NC
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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.