Evidence map›Paper›PMID 38166831›Full record

ArticleBMC infectious diseases2024

Time series analysis and short-term forecasting of monkeypox outbreak trends in the 10 major affected countries.

Tahir Munir, Maaz Khan, Salman Arif Cheema, Fiza Khan, Ayesha Usmani, Mohsin Nazir

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
5.6field-weighted citation impact, top 4% 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

10 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
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

6 authors at 2 institutions in 1 country.

Tahir MunirDepartment of Anaesthesiology, Aga Khan University Hospital, Private Wing, Second Floor, Stadium Road, PO. Box 3500, Karachi, 74800, Pakistan. tahirmunir677@yahoo.com.
Maaz KhanDepartment of Anaesthesiology, Aga Khan University Hospital, Private Wing, Second Floor, Stadium Road, PO. Box 3500, Karachi, 74800, Pakistan.
Salman Arif CheemaDepartment of Applied Sciences, National Textile University, Faisalabad, 37610, Pakistan.
Fiza KhanDepartment of Anaesthesiology, Aga Khan University Hospital, Private Wing, Second Floor, Stadium Road, PO. Box 3500, Karachi, 74800, Pakistan.
Ayesha UsmaniDepartment of Anaesthesiology, Aga Khan University Hospital, Private Wing, Second Floor, Stadium Road, PO. Box 3500, Karachi, 74800, Pakistan.
Mohsin NazirDepartment of Anaesthesiology, Aga Khan University Hospital, Private Wing, Second Floor, Stadium Road, PO. Box 3500, Karachi, 74800, Pakistan.
Aga Khan University Hospital · PKNational Textile University · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundConsidering the rapidly spreading monkeypox outbreak, WHO has declared a global health emergency. Still in the category of being endemic, the monkeypox disease shares numerous clinical characters with smallpox. This study focuses on determining the most effective combination of autoregressive integrated moving average model to encapsulate time dependent flow behaviour of the virus with short run prediction.

methodsThis study includes the data of confirmed reported cases and cumulative cases from eight most burdened countries across the globe, over the span of May 18, 2022, to December 31, 2022. The data was assembled from the website of Our World in Data and it involves countries such as United States, Brazil, Spain, France, Colombia, Mexico, Peru, United Kingdom, Germany and Canada. The job of modelling and short-term forecasting is facilitated by the employment of autoregressive integrated moving average. The legitimacy of the estimated models is argued by offering numerous model performance indices such as, root mean square error, mean absolute error and mean absolute prediction error.

resultsThe best fit models were deduced for each country by using the data of confirmed reported cases of monkeypox infections. Based on diverse set of performance evaluation criteria, the best fit models were then employed to provide forecasting of next twenty days. Our results indicate that the USA is expected to be the hardest-hit country, with an average of 58 cases per day with 95% confidence interval of (00-400). The second most burdened country remained Brazil with expected average cases of 23 (00-130). The outlook is not much better for Spain and France, with average forecasts of 52 (00-241) and 24 (00-121), respectively.

conclusionThis research provides profile of ten most severely hit countries by monkeypox transmission around the world and thus assists in epidemiological management. The prediction trends indicate that the confirmed cases in the USA may exceed than other contemporaries. Based on the findings of this study, it remains plausible to recommend that more robust health surveillance strategy is required to control the transmission flow of the virus especially in USA.

Indexed as

Models, StatisticalMpox, MonkeypoxDisease OutbreaksForecastingHumansTime FactorsARIMAForecastingMonkeypoxTime Series ModellingViral Transmission

Identifiers

PMID38166831
PMCPMC10762824
OpenAlexW4390509207

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.