Evidence map›Paper›PMID 41678552›Full record

ArticlePloS one2026

Short-term forecasting and impact analysis of COVID-19 and the stock market in Morocco using ARIMA.

N'Adoi Aboagye, Saralees Nadarajah

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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5 · Who and what money

Authors and funding

2 authors.

N'Adoi AboagyeDepartment of Mathematics, University of Manchester, Manchester, United Kingdom.
Saralees NadarajahDepartment of Mathematics, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0001-7763-5862

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to predict the short-term trends of confirmed COVID-19 cases and the MASI stock index in Morocco using the ARIMA method. COVID-19 case data were obtained from Our World in Data, while MASI stock market data were obtained from Investing.com. The dataset covered the period from March 2, 2020 to April 28, 2022. To develop the predictive model, data from March 2, 2020 to April 28, 2022, were used for training. Data from April 22, 2022 to April 28, 2022, were used for model fitting for COVID-19 cases, and from April 25, 2022 to April 29, 2022, for the MASI index. Based on these models, we conducted short-term forecasts for April 29, 2022 to May 1, 2022, for COVID-19 cases, and May 4, 2022 to May 6, 2022, for the MASI index. The forecasting accuracy was mainly evaluated using the mean absolute percentage error (MAPE). Furthermore, we applied the Granger causality test to investigate the potential directional relationship between COVID-19 case trends and MASI index fluctuations. To the best of our knowledge, this is the first study to perform short-term forecasting of both COVID-19 cases and the MASI stock index in Morocco while also assessing their dynamic interplay, providing a novel contribution to the intersection of epidemiological and financial modeling in the region.

Indexed as

COVID-19InvestmentsForecastingHumansMoroccoPandemicsPrediction AlgorithmsSARS-CoV-2

Identifiers

PMID41678552
PMCPMC12900332

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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.