📄 medicine

Analysis of spatial-temporal distribution and influencing factors of pulmonary tuberculosis in Mainland China based on geographic information system, 2014-2023

This study analyzes 2014–2023 data to reveal that while pulmonary tuberculosis incidence and mortality in Mainland China have generally declined, the disease exhibits significant spatial clustering in the northwest and humid, economically developed regions, with incidence negatively associated with health expenditure and medical staffing but positively linked to illiteracy rates.

Original authors: Xinzhu Xiao, Yuping Zhan, Yunfei Chen, Qichao Fan, Junjin Liu, Jiaofeng Huang, Haibo Ding

Published 2026-07-02

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Xinzhu Xiao, Yuping Zhan, Yunfei Chen, Qichao Fan, Junjin Liu, Jiaofeng Huang, Haibo Ding

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine China as a giant, 31-room house where a sneaky, invisible guest named Pulmonary Tuberculosis (PTB) has been living for the last decade. This paper is like a detailed map and a detective's notebook that tracks where this guest has been hiding between 2014 and 2023, how many people it has bothered, and what factors in the house seem to help or hinder its stay.

Here is the story of that investigation, broken down into simple parts:

1. The Big Picture: The Guest is Leaving (But Not Quietly)

For ten years, the "guest" (PTB) has been slowly packing its bags. The number of new cases and deaths has gone down overall. In fact, for ten years straight, PTB was the second most common infectious disease in China, right behind the others. By 2023, it dropped to third place in terms of deaths, finally letting viral hepatitis take the top spot.

However, the guest didn't leave all at once.

The Pandemic Pause: During the height of the COVID-19 pandemic (2020–2022), the numbers dropped sharply. Think of it like everyone staying home and wearing masks; the TB germs couldn't travel as easily.
The 2023 Rebound: In 2023, the numbers ticked back up. The authors suggest this is like opening the front door after a long lockdown. People started traveling again, and doctors got better at finding the cases they might have missed during the chaos.

2. The Map: Where is the Guest Hiding?

If you look at a map of China, the guest isn't spread out evenly like sprinkles on a cake. It's clustered in specific corners.

The "High-Risk" Zone: The guest loves the Northwest. Specifically, the regions of Xinjiang, Tibet, Qinghai, and Guizhou are like the guest's favorite hotel rooms. These areas have the highest number of cases.
The "Low-Risk" Zone: The East Coast and North China (places like Shanghai, Beijing, and Tianjin) are like the guest-free zones. These areas have the lowest numbers.
The Clustering Effect: The study used a special digital tool (like a heat map) to show that if one room has a lot of TB, the rooms right next to it usually do too. It's a "clumping" effect, especially in the northwest.

3. The Mystery of the "Rich" and the "Poor"

The researchers looked at what makes a room more attractive to the guest. They found some surprising connections:

Money (GDP) is a Double-Edged Sword: You might think rich areas would be safer, but the study found that areas with higher Per Capita GDP (more money per person) sometimes had more TB.
- The Analogy: Imagine a busy train station. Rich areas are like the main station where people from all over the country (including high-risk areas) come to work. These travelers might carry the germ with them. Also, rich areas have better doctors who find and report the cases more accurately. So, the high numbers might actually mean the system is working well, not that the disease is worse.
Education Matters: Areas with higher illiteracy rates (more people who can't read) tended to have more TB.
- The Analogy: If you can't read the warning signs or understand the instructions on how to stay healthy, it's harder to avoid the guest. Better education acts like a shield.
Healthcare is the Bouncer: Areas with more doctors and nurses and more money spent on health had fewer cases.
- The Analogy: Think of healthcare workers as bouncers at a club. The more bouncers you have, the better they are at spotting the troublemaker (TB) early and kicking them out (treating them) before they infect others.
Medical Buildings Don't Matter: Interestingly, just having more buildings (hospitals) didn't change the numbers. It's not about the size of the building; it's about the people inside it.

4. The Weather Factor

The researchers also checked if the weather was inviting the guest.

Humidity: They found a link between humidity (moist air) and TB.
- The Analogy: TB germs travel on tiny droplets of water in the air. Think of humidity like a "slippery slide" that helps these droplets stay in the air longer and float around, making it easier for the guest to jump from person to person.
Temperature and Sun: Surprisingly, hot/cold temperatures, rain, and sunshine didn't seem to matter much in this study.

5. The Conclusion: How to Evict the Guest

The paper concludes that to get rid of this guest for good, China needs a multi-pronged approach:

Focus on the Northwest: Send extra resources to the high-risk clusters in the west.
Hire More Bouncers: Increase the number of health workers and spending on healthcare.
Open the Books: Fight illiteracy so people understand how to protect themselves.
Watch the Air: Keep environments dry to stop the germs from floating around.

The Catch (Limitations):
The authors admit they looked at the data from a "bird's eye view" (province-level averages). They couldn't see exactly what happened to individual people, so they can't say for sure that "being poor causes TB" or "being rich causes TB." They also missed some factors like how much people travel or the specific strains of drug-resistant TB.

In short, TB in China is getting better, but it's still a stubborn guest that hides in specific corners, influenced by money, education, and the humidity in the air.

Technical Summary: Spatiotemporal Distribution and Influencing Factors of Pulmonary Tuberculosis in Mainland China (2014–2023)

Problem Statement
Despite significant progress in tuberculosis (TB) control, China remains one of the 30 high-TB-burden countries globally, accounting for approximately 6.5% of the global estimated incidence. Pulmonary tuberculosis (PTB) continues to rank second among notifiable infectious diseases in China regarding both incidence and mortality. While national incidence and mortality rates have declined over the past few decades, significant regional heterogeneity persists, with a "high in the west, low in the east" distribution pattern. Furthermore, the complex interplay of socioeconomic, medical, and climatic factors influencing PTB transmission remains a challenge for formulating precise, targeted prevention and control strategies. This study addresses the need to analyze the spatiotemporal evolution of PTB in Mainland China from 2014 to 2023 and to identify the specific factors driving these patterns to guide future public health interventions.

Methodology
The study utilized an ecological design based on aggregate data from 31 provinces, autonomous regions, and municipalities in Mainland China (excluding Taiwan, Hong Kong, and Macao) covering the period from 2014 to 2023.

Data Sources: PTB incidence and mortality data were extracted from the China Health and Family Planning Statistical Yearbook (2014–2017) and the China Health Statistics Yearbook (2018–2023). Socioeconomic and meteorological variables, including per capita Gross Domestic Product (PCGDP), illiteracy rates, health expenditure, medical institution density, health personnel density, temperature, humidity, precipitation, and sunshine duration, were obtained from the China Statistical Yearbook.
Spatial Analysis: ArcGIS 10.8 was employed to map the spatial distribution of PTB incidence. Global spatial autocorrelation was assessed using the Moran's I index via GeoDa 1.12 to determine clustering trends, utilizing Monte Carlo simulation for significance testing. Local Indicators of Spatial Association (LISA) were calculated to identify specific high-high (hot spots) and low-low (cold spots) clustering patterns.
Correlation Analysis: Spearman rank correlation analysis was performed using SPSS to evaluate the relationship between PTB incidence rates and the selected socioeconomic and meteorological variables. Statistical significance was set at $P < 0.05$ .

Key Results

Temporal Trends: From 2014 to 2023, the average annual PTB incidence in Mainland China was 54.18 per 100,000 population. The overall trend showed a decline, with the highest incidence in 2014 (65.63/100,000) and the lowest in 2022 (39.76/100,000). However, a rebound occurred in 2023, with new cases rising to 613,091 (43.49/100,000). Mortality rates fluctuated, peaking in 2018 and reaching a low in 2021 before rising again in 2023. Despite the decline, PTB remained the second most common notifiable infectious disease by incidence throughout the decade.
Spatial Distribution: A significant positive spatial autocorrelation was observed for PTB incidence across all years (Moran's I > 0, $P < 0.001$ $P < 0.001$ ), indicating a clustered distribution.
- Regional Disparities: The western region consistently exhibited the highest incidence rates (average 78.69/100,000), followed by the central region (55.02/100,000), with the eastern region having the lowest (40.94/100,000).
- Clustering Patterns: Local analysis identified "high-high" clustering primarily in the northwest (Xinjiang and Tibet) and, in the 2020–2023 period, extending to Yunnan and Guangxi. "Low-low" clustering was observed in North China and eastern coastal provinces (e.g., Shanghai, Tianjin, Shandong).
Influencing Factors:
- Socioeconomic: A notable positive correlation was found between PTB incidence and regional PCGDP in various years, and a positive correlation with illiteracy rates in specific years (2020, 2022, 2023). Conversely, per capita health expenditure and the number of health technical personnel per 1,000 population showed negative correlations with incidence in certain years. The number of medical institutions per capita showed no significant correlation.
- Climatic: PTB incidence demonstrated a positive correlation with relative humidity in specific years (2015, 2017). No significant correlations were found with average temperature, precipitation, or sunshine duration.

Key Contributions
This study provides a comprehensive spatiotemporal analysis of PTB in China over a critical decade, identifying specific high-risk clusters that require targeted intervention. It quantifies the relationship between PTB incidence and a broad spectrum of determinants, highlighting that while economic development (PCGDP) correlates with higher reported incidence (potentially due to migration and detection capabilities), increased health investment and personnel are associated with reduced incidence. The research also clarifies the role of climatic factors, specifically identifying humidity as a potential risk factor while ruling out others like temperature and precipitation.

Significance and Claims
The authors claim that the study offers essential data support for governments and public health institutions to refine PTB prevention and control strategies. By identifying distinct spatiotemporal clustering patterns—particularly the persistence of high incidence in the northwest and the rebound in 2023—the study underscores the necessity of moving beyond uniform national policies toward region-specific interventions.

The paper posits that effective control requires a multi-faceted approach:

Targeted Resource Allocation: Focusing on high-incidence clusters in Xinjiang, Tibet, and Yunnan.
Strengthening Health Systems: Increasing per capita health expenditure and the density of health technical personnel to improve early detection and treatment.
Education and Literacy: Addressing illiteracy to improve health literacy and treatment compliance.
Environmental Considerations: Acknowledging the potential role of humidity in transmission dynamics.

The study concludes that while China has made progress, the rebound in 2023 and the persistent regional disparities necessitate continued, precise efforts to achieve the WHO "End TB Strategy" goals. The authors acknowledge limitations, including the use of aggregate data which may lead to ecological fallacy, variations in local monitoring quality, and the exclusion of certain risk factors like population mobility and drug resistance prevalence.