Data-Driven Insights on Malaria: A Case Study on Trends, Burden, and Forecasting

Introduction

In this case study, we analyze the malaria burden globally, with a specific focus on Tanzania. We examine trends in malaria deaths worldwide and Tanzania’s relative position in the burden. Additionally, we investigate the trends in malaria incidence and mortality rates in Tanzania since 2000, along with the spatial distribution of malaria prevalence in children under five. Moreover, we assess the coverage of key malaria interventions, such as bed nets, indoor spraying, malaria diagnostic tools, and recommended treatment. Lastly, we provide time series forecasts for malaria incidence and mortality until 2030.

The aim of this analysis is to communicate valuable insights into the malaria burden, intervention coverage, and Tanzania’s progress towards global malaria goals, facilitating the development of effective strategies to combat this disease and improve public health outcomes.

Data used for this analysis were retrieved from the WHO Global Health Observatory (GHO) website https://www.who.int/data/gho/data/indicators/ and the Demographic Health Survey (DHS) website https://www.dhsprogram.com/data/dataset_admin/login_main/.
All data were cleaned and analyzed using R programming, and all the codes used for data cleaning and analysis can be found here https://github.com/nyandele/Malaria_Case_Study

1. Trends in Malaria Deaths

1.1. Malaria Deaths Worldwide

Fig 01 shows a declining trend in global malaria deaths from 2000 to 2019, dropping from 850,000 to 550,000 deaths.
However in 2020, malaria deaths increased by 12% due to COVID-19 disruptions, emphasizing the need for urgent action to address the upward trend¹.
The African region consistently bears over 95% of global malaria deaths, highlighting the necessity for increased efforts and investments in this region¹.

1.2. Malaria deaths in the African region, with a focus on Tanzania

In the African region, five countries often contribute over 50% of the malaria death toll². Fig 02 depicts the trend of the top five countries since 2010.
Tanzania joined the list in 2015 and has remained among the top five since then, accounting for approximately 8% of the death toll (Fig 02).
This indicates a concerning upward trend in the malaria burden in Tanzania relative to other African countries, emphasizing the urgency for immediate action to address this issue.

1.3. Malaria incidence and mortality in Tanzania

Fig 3a and 3b depict the trends in malaria incidence and mortality indicators in Tanzania, comparing them to global trends.
Globally, these indicators have remained low and declined steadily. In Tanzania, the decline has significantly slowed since 2015, with a slight upward trend in 2020 due to COVID-19 disruptions and challenges in humanitarian services.
These findings emphasize the need for action to address new challenges in curbing malaria infections, especially as malaria epidemiology changes when transmission declines (as indicated by the stalled progress since 2015).

1.4. Spatial distribution of malaria prevalence in children under 5 years of age in Tanzania

Fig 04 reveals the uneven geographic distribution of the malaria burden.
Our analysis focused on malaria prevalence in the most vulnerable group, children under five, as an indicator of the overall national burden. Fig 04 demonstrates that the burden is concentrated in the lake and western zones, as well as the southern zone of Tanzania.
This emphasizes the need for targeted interventions in these zones due to factors such as high mosquito breeding grounds, climate conditions conducive to increased transmission, and potential variations in the quality of public health services^2,3.

2. Trends in Coverage of Malaria Interventions

2.1: Recent trends in malaria interventions - malaria treatment, bed nets and insecticide spraying

Fig 05 displays trends in coverage indicators for malaria interventions, including the number of individuals treated with recommended malaria therapy and protected by insecticide-treated bed nets (ITNs) and indoor residual spraying (IRS).
IRS coverage shows a significant decline from 2019 to 2020, decreasing from 2,850,000 to 2,500,000 individuals. This highlights disruptions in intervention coverage due to the COVID-19 pandemic.
The trends in malaria cases treated and ITN coverage also demonstrate a consistent decrease since 2018, from 7 million to 4 million cases treated and 58.5% to 53.5% ITN coverage. This suggests the impact of COVID-19 and potentially other factors such as operational challenges and lack of awareness and education.
While the limited observation period of 3 years may not capture the complete variability or long-term trends, these visualizations provide a basic understanding of recent coverage trends, which appear to be declining.

2.2: Trends in malaria interventions - malaria diagnoses using microscopy and mRDT tools

In Fig 06, we examine trends in malaria diagnoses, focusing on a shift in diagnostic methods. Prior to 2014, microscopy was the primary method of diagnosis, resulting in a significant number of missed cases, as depicted in Figure 06. Estimated malaria cases consistently exceeded those confirmed by microscopy.
The introduction of malaria rapid diagnostic tests (mRDT) led to a substantial increase in diagnosed cases, as shown in the trend from 2015 to 2020.
Despite this improvement, a considerable number of malaria cases still remain undiagnosed. This highlights the need for more sensitive and advanced diagnostic tools to identify and treat all cases, ultimately reducing the disease reservoir and advancing progress towards elimination.

3. Time Series Forecasting of Malaria Incidence and Mortality

Utilizing ARIMA models in R, we forecasted malaria incidence and mortality trends in Tanzania until 2030. The forecasts indicate Tanzania’s substantial deviation from the Global Technical Strategy (GTS) malaria targets for both indicators. The GTS targets aim to achieve a 75% reduction in malaria incidence and a 90% reduction in malaria mortality by 2025 and 2030 respectively, relative to the 2015 levels².

3.1: Current and Forecasted Trends in Malaria Incidence in Tanzania

Fig 07 depicts Tanzania’s failure to meet the GTS targets for malaria incidence in 2025 and 2030.
The forecast suggests that without immediate action, these targets will not be achieved.
Urgent and intensified action is required to combat malaria and align with other countries that have successfully met these global targets.

3.2: Current and Forecasted Trends in Malaria Mortality in Tanzania

Fig 08 illustrates Tanzania’s inability to meet the GTS targets for malaria mortality in both 2025 and 2030. The forecast emphasizes the need for immediate action to prevent further loss of lives due to malaria.
Without urgent and intensified efforts, the targets for reducing and ultimately eliminating malaria-related deaths will remain out of reach.
It is crucial for Tanzania to take decisive action and align with other countries that have successfully achieved these global targets.

Conclusion

In conclusion, Malaria remains a significant challenge in Africa and a persistent burden for Tanzania. Incidence and mortality rates in Tanzania have shown a stagnant or slight upward trend since 2015. Spatial distribution analysis reveals specific zones with a higher prevalence, thus requiring targeted interventions. Coverage of malaria interventions has declined, potentially due to funding limitations, operational challenges, and the impact of COVID-19. Improved diagnostic methods have led to increased malaria diagnoses, but there is still a need for more sensitive tools. Furthermore, forecasts indicate Tanzania falling significantly behind the GTS targets for malaria incidence and mortality.

Urgent action is needed to curb malaria, meet global targets, and reduce the burden on the population. Increased funding and resources are required to support prevention and control efforts in Tanzania. Strengthening healthcare systems and raising awareness about malaria prevention can help address the challenges, and collaboration with other countries that have successfully achieved global targets can provide valuable insights and guidance.

Future Enhancements:

Potential future enhancements to this case study include incorporating additional datasets for a more comprehensive analysis of the malaria burden and coverage of interventions, exploring advanced time series forecasting models such as SARIMA to capture more complex patterns and seasonality effects on the malaria burden, and the use of interactive dashboards and web applications to enhance accessibility and usability of the data.

References

World Malaria Report https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2022
Global Technical Strategy for Malaria https://www.who.int/docs/default-source/documents/global-technical-strategy-for-malaria-2016-2030.pdf
Tanzania Malaria Indicator Survey https://dhsprogram.com/pubs/pdf/MIS31/MIS31.pdf