Evolutionary trends of the COVID-19 epidemic and effectiveness of government interventions in Nigeria: A data-driven analysis

  1. Oluwakemi O Odukoya
  2. Ismaila A Adeleke
  3. Chris S Jim
  4. Brenda C Isikekpei
  5. Chiamaka M Obiodunukwe
  6. Folusho E Lesi
  7. Akin O Osibogun
  8. Folasade T Ogunsola

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Abstract

Background

Nigeria became the first sub Saharan African country to record a case of COVID-19 after an imported case from Italy was confirmed on February 27, 2020. Moving averages and the Epidemic Evaluation Indices (EEI) are two important but complementary methods useful in monitoring epidemic trends, they can also serve as a useful guide for policy makers and inform the timing of decisions on preventive measures. The objectives of this paper are to graphically depict the trends of new COVID-19 cases nationally and in two key States (Lagos and Kano) and the Federal Capital Territory (FCT) using the moving averages and the EEI. In addition, we examined the effects of government’s public health interventions on the spread of COVID-19 and appraise the progress made so far in addressing the challenges of COVID-19 in Nigeria.

Methods

We used data on new cases of COVID-19 from public sources released by the Nigeria Center for Disease Control (NCDC) from the 27 th February 2020, when the first case was recorded, to 11 th May, 2020, one week after the lockdowns in Lagos and the FCT were lifted. We computed moving averages of various orders, the log transformations of the moving averages and then the EEIs of new COVID-19 cases for Nigeria as a whole, and then for two of the most affected states i.e. Lagos and Kano, as well as the Federal Capital Territory (FCT). Then, we plotted graphs to depict these indices and show the epidemic trends for COVID-19 in each scenario.

Results

Nationally, the number of new cases of COVID-19 showed an initial gradual rise from the first reported case on the 27 th February 2020. However, by the second week in April, these numbers began to show a relatively sharper increase and this trend has continued till date. Similar trends were observed in Lagos state and the FCT. The rate of growth of the logarithm-transformed moving average in the period leading to, and including the lockdowns reduced by a factor of 0.65. This suggests that the policies put in place by the government including the lockdown measures in Lagos and the FCT may have had a positive effect on the development of new cases of COVID-19 in Nigeria. Nationally and in Lagos, the EEIs of the COVID-19 cases started off on very high notes, however, the effects of the lockdown gradually became evident by the end of April and early May 2020, as the EEIs headed closer to 1.0. In all case scenarios, the EEIs are still above 1.0.

Conclusions and recommendations

The number of new cases of COVID-19 has been on a steady rise since the first reported case. In Nigeria especially across the two states and the FCT, public health interventions including the lockdown measures appear to have played a role in reducing the rate of increase of new infections. The EEIs are still above 1.0, suggesting that despite the progress that appears to have been made, the epidemic is still evolving and Nigeria has not yet reached her peak for COVID-19 cases. We recommend that aggressive public health interventions and restrictions against mass gatherings should be sustained.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.29.20110098: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    It however has some limitations, Firstly, moving averages are often affected by extreme values and outliers, however, our data did not have significant outliers or extreme values. Secondly, logarithmic transformations of the moving averages might be problematic when several zero entries on consecutive days producing an average of zero exist in the dataset. This was taken care of by adding 1 to the moving averages before computing the logarithms. Another limitation is that our EEIs were computed based on a singular moving average order 7. There may be a need to consider the comparison of other orders to check for consistency in future studies. Further, the data used to develop our models are based on publicly available data from the NCDC. As at the time we constructed our charts, only 29,408 tests had been conducted nationally, indicating a possible under estimation of our findings. Also, the limited data from Kano (the first case was on the 11th April 2020) may make inferences for Kano a little premature. Finally, all data presented are as at the 12th May 2020, events after this are not included in our model, however, we hope to report an update of our findings over time. Conclusion and recommendations: The number of new cases of COVID-19 has been on a steady rise since the first reported cases on the 27th February 2020. Public health interventions including the lockdown measures in Lagos and the FCT appear to have assisted in reducing the rate of increase of new infections. ...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.05.29.20110098v1 on medRxiv