Evidence map›Paper›PMID 40468189›Full record

ArticleBMC infectious diseases2025

Time series modelling and forecasting of mpox incidence and mortality in Nigeria.

Emmanuel Afolabi Bakare, Oluwaseun Akinlo Mogbojuri, Dolapo Oluwaseun Oniyelu, Afeez Abidemi, Deborah Oluwatobi Daniel, Idowu Isaac Olasupo, Samuel Abidemi Osikoya, Aaron Onyebuchi Nwana, Ronke Dorcas Olorunfemi, Samson Oluwafemi Olagbami

Abstract read
In one paragraph

Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

10 authors.

Emmanuel Afolabi BakareInternational Centre for Applied Mathematical Modelling and Data Analytics, Federal University Oye-Ekiti, Ekiti State, Nigeria. emmanuel.bakare@fuoye.edu.ng.
Oluwaseun Akinlo MogbojuriInternational Centre for Applied Mathematical Modelling and Data Analytics, Federal University Oye-Ekiti, Ekiti State, Nigeria.
Dolapo Oluwaseun OniyeluInternational Centre for Applied Mathematical Modelling and Data Analytics, Federal University Oye-Ekiti, Ekiti State, Nigeria.
Afeez AbidemiInternational Centre for Applied Mathematical Modelling and Data Analytics, Federal University Oye-Ekiti, Ekiti State, Nigeria.
Deborah Oluwatobi DanielInternational Centre for Applied Mathematical Modelling and Data Analytics, Federal University Oye-Ekiti, Ekiti State, Nigeria.
Idowu Isaac OlasupoInternational Centre for Applied Mathematical Modelling and Data Analytics, Federal University Oye-Ekiti, Ekiti State, Nigeria.
Samuel Abidemi OsikoyaInternational Centre for Applied Mathematical Modelling and Data Analytics, Federal University Oye-Ekiti, Ekiti State, Nigeria.
Aaron Onyebuchi NwanaInternational Centre for Applied Mathematical Modelling and Data Analytics, Federal University Oye-Ekiti, Ekiti State, Nigeria.
Ronke Dorcas OlorunfemiInternational Centre for Applied Mathematical Modelling and Data Analytics, Federal University Oye-Ekiti, Ekiti State, Nigeria.
Samson Oluwafemi OlagbamiInternational Centre for Applied Mathematical Modelling and Data Analytics, Federal University Oye-Ekiti, Ekiti State, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The World Health Organization (WHO) declared mpox a Public Health Emergency of International Concern (PHEIC) twice, in response to the global outbreak, first in May 2022 and again in August 2024, after a span of 2 years and 3 months. African countries continue to be a hotspot for the ongoing mpox outbreaks and Nigeria has contributed substantially in exporting the virus to other countries, highlighting the need for an in-depth analysis of outbreak patterns and forecasting to inform public health policy. This study used the Auto-Regressive Integrated Moving Average (ARIMA) model to perform a 14-month forecast of mpox cases and mortality in Nigeria using mpox monthly routine data. The data were split into two portions; 70% for training, used to estimate the parameters of the forecasting model and 30% for testing, used to evaluate the model's accuracy. Wavelet analysis was used to decompose the time series into its various frequency components, enabling a multi-resolution analysis of the data. The ARIMA model forecasted an average of 13 mpox cases per month and zero mortality over a 14-month period. The wavelet power spectrum revealed a strong annual cycle between June 2022 and June 2023. In order to sustain the forecasted downward trend in mpox cases in the coming months, it is essential that the National Mpox Technical Working Group (TWG) of Nigeria Centre for Disease Control and Prevention (NCDC) continue to coordinate scale up of vaccine coverage and improve surveillance especially in high risk area. The findings will ultimately improve focused interventions and knowledge of mpox outbreak patterns by guiding public health policy, allocating resources optimally, and preparing health systems for potential outbreaks.

Indexed as

Disease OutbreaksMpox, MonkeypoxForecastingHumansIncidenceModels, StatisticalNigeriaARIMAForecastingMpoxTime series analysisWavelet analysis

Identifiers

PMID40468189
PMCPMC12139326

What OpenQuestion holds

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LicenceCC BY
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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.