Understanding the Spread of Tuberculosis in North Sumatra

Oct 13, 2025 by talynt.org 66 views

Understanding the Spread of Tuberculosis in North Sumatra

Spatial analysis plays a crucial role in understanding the spread of disease, especially in this modern era. Location is a key factor in determining the disease control strategy and its impact. Tuberculosis (TB) is a disease that is still a serious threat in Indonesia, including in North Sumatra. The disease caused by the bacterium Mycobacterium tuberculosis places Indonesia as a country with the third largest number of TB sufferers in the world after India and China.

In 2020, there were 845,000 TB sufferers in Indonesia, with 93,000 of them died. This number shows the urgency of handling TB effectively. For this reason, this study analyzed the pattern of distribution of TB in North Sumatra in 2017 using the spatial analysis method. The study aimed to identify the areas with high and low TB rates, and to understand the spatial autocorrelation between these areas.

Revealing the Pattern of Spread with the Moran and LISA Index

This study applies the Moran and Local Indicator of Spatial Association (LISA) index to measure spatial autocorrelation in the spread of TB. Spatial autocorrelation measures spatial dependence between adjacent locations. The results of the analysis showed the presence of positive autocorrelation in the data on the distribution of TB in North Sumatra. That is, there is a tendency to group areas with high number of TB sufferers. This shows that areas that have many TB sufferers tend to be close to areas that also have a high number of sufferers.

The Moran index is a statistical measure that calculates the correlation between the values of a variable and its spatial neighbors. The LISA index is a more advanced measure that identifies clusters of high and low values. The results of the analysis showed that the Moran index was 0.5, indicating a moderate level of spatial autocorrelation. The LISA index identified several clusters of high and low TB rates, which are discussed in the next section.

Vulnerable Zone and Safe Zone in North Sumatra

Based on the results of LISA's analysis, this study identified several areas with significant autocorrelation rates. Deli Serdang and Medan City are categorized as vulnerable zones, with high number of TB sufferers and are around the area with a high number of sufferers. Conversely, Nias, West Nias, North Nias, and Gunung Sitoli are included in the safe zone category, with a lower number of TB sufferers and close to areas that also have a low number of sufferers.

The vulnerable zones require special attention with a focus on increasing early detection, increasing access to health services, and increasing education and public awareness. The safe zones need to remain monitored and maintained, with efforts to prevent and educate the community in the area to prevent the emergence of new cases and maintain safe status from the distribution of TB.

Implications for TB Control Strategies

The results of this study provide important information in developing more effective TB control strategies in North Sumatra. The study highlights the need to focus on vulnerable zones, such as Deli Serdang and Medan City, with a focus on increasing early detection, increasing access to health services, and increasing education and public awareness.

The study also highlights the need to maintain the safe zones, such as Nias, West Nias, North Nias, and Gunung Sitoli, with efforts to prevent and educate the community in the area to prevent the emergence of new cases and maintain safe status from the distribution of TB.

The Need to Increase Data and Collaboration

This study uses TB data in 2017. To get a more comprehensive understanding, the latest and more complete data is needed. The data can be used to map the vulnerable and safe zone, as well as evaluating the effectiveness of the TB control strategy that has been applied.

Collaboration between institutions, both the government, health organizations, and the community, is also very important to increase the effectiveness of TB handling. The division of tasks and clear responsibilities, as well as synergy in the implementation of TB control programs, is the key to achieving the goal of Elimination of TB in North Sumatra.

Conclusion

This study demonstrates the importance of spatial analysis in understanding the spread of TB in North Sumatra. The study applies the Moran and LISA index to measure spatial autocorrelation in the spread of TB and identifies several areas with significant autocorrelation rates.

The study highlights the need to focus on vulnerable zones, such as Deli Serdang and Medan City, with a focus on increasing early detection, increasing access to health services, and increasing education and public awareness. The study also highlights the need to maintain the safe zones, such as Nias, West Nias, North Nias, and Gunung Sitoli, with efforts to prevent and educate the community in the area to prevent the emergence of new cases and maintain safe status from the distribution of TB.

The study emphasizes the need to increase data and collaboration between institutions to increase the effectiveness of TB handling. The division of tasks and clear responsibilities, as well as synergy in the implementation of TB control programs, is the key to achieving the goal of Elimination of TB in North Sumatra.

Recommendations

Based on the findings of this study, the following recommendations are made:

Increase early detection: Through the screening and periodic inspection programs, especially in areas with high population density and poor socio-economic conditions.
Increase access to health services: Ensuring the availability of quality and affordable TB treatment services in the region.
Increase education and public awareness: Health campaign to increase knowledge about TB, symptoms, ways of transmission, and the importance of treatment.
Maintain safe zones: Efforts to prevent and educate the community in the area to prevent the emergence of new cases and maintain safe status from the distribution of TB.
Increase data and collaboration: The latest and more complete data is needed to map the vulnerable and safe zone, as well as evaluating the effectiveness of the TB control strategy that has been applied.
Collaboration between institutions: The division of tasks and clear responsibilities, as well as synergy in the implementation of TB control programs, is the key to achieving the goal of Elimination of TB in North Sumatra.

Q: What is spatial analysis and how is it used in this study?

A: Spatial analysis is a statistical method used to analyze and understand the relationships between geographic locations and the data associated with those locations. In this study, spatial analysis is used to understand the spread of tuberculosis (TB) in North Sumatra and to identify areas with high and low TB rates.

Q: What is the Moran index and how is it used in this study?

A: The Moran index is a statistical measure that calculates the correlation between the values of a variable and its spatial neighbors. In this study, the Moran index is used to measure spatial autocorrelation in the spread of TB in North Sumatra.

Q: What is the LISA index and how is it used in this study?

A: The LISA index is a more advanced measure that identifies clusters of high and low values. In this study, the LISA index is used to identify areas with significant autocorrelation rates and to understand the spatial relationships between these areas.

Q: What are the vulnerable zones and safe zones identified in this study?

A: The vulnerable zones identified in this study are Deli Serdang and Medan City, which have high number of TB sufferers and are around the area with a high number of sufferers. The safe zones identified in this study are Nias, West Nias, North Nias, and Gunung Sitoli, which have a lower number of TB sufferers and close to areas that also have a low number of sufferers.

Q: What are the implications of this study for TB control strategies in North Sumatra?

A: The study highlights the need to focus on vulnerable zones, such as Deli Serdang and Medan City, with a focus on increasing early detection, increasing access to health services, and increasing education and public awareness. The study also highlights the need to maintain the safe zones, such as Nias, West Nias, North Nias, and Gunung Sitoli, with efforts to prevent and educate the community in the area to prevent the emergence of new cases and maintain safe status from the distribution of TB.

Q: What are the limitations of this study?

A: The study uses TB data in 2017, which may not reflect the current situation. The study also relies on secondary data, which may not be comprehensive or accurate.

Q: What are the recommendations of this study?

A: The study recommends increasing early detection, increasing access to health services, and increasing education and public awareness in vulnerable zones. The study also recommends maintaining safe zones with efforts to prevent and educate the community in the area to prevent the emergence of new cases and maintain safe status from the distribution of TB.

Q: What are the future directions of this study?

A: The study suggests that future research should focus on collecting more comprehensive and accurate data, including data on the social and economic determinants of health. The study also suggests that future research should explore the use of spatial analysis in other areas of public health, such as the spread of other infectious diseases.

Q: What are the implications of this study for policy and practice?

A: The study highlights the need for policymakers and practitioners to consider the spatial relationships between geographic locations and the data associated with those locations when developing and implementing public health interventions. The study also highlights the need for policymakers and practitioners to prioritize vulnerable zones and to maintain safe zones to prevent the emergence of new cases and maintain safe status from the distribution of TB.

Q: What are the contributions of this study to the field of public health?

A: The study contributes to the field of public health by providing a spatial analysis of the spread of TB in North Sumatra and by identifying areas with high and low TB rates. The study also contributes to the field of public health by highlighting the need for policymakers and practitioners to consider the spatial relationships between geographic locations and the data associated with those locations when developing and implementing public health interventions.