knitr::include_graphics("/Users/guanr./Desktop/Qing Empire.png")

map above: the Chinese Empire (Qing) in 1910. Manchuria is the northeastern part of China.

The Manchurian plague during 1910-1911 was a notable pandemic event in the early twentieth century, which had a major impact on state-building, economic development, and the geopolitical order of northeastern China (i.e., Manchuria). The plague pandemic killed about 60,000 people in dozens of counties and cities across Manchuria. The source of the plague was the region of Siberia under the Russian Empire’s ruling, where Chinese and Russian merchants engaged in the traditional and lucrative fur trade. In the process, hunters and traders inevitably came into close contact with many organisms that carried the plague pathogen, such as marmots and martens. As the cross-border trade flowed, mainly pushed traders and hunters, the plague was spread to Manchuria through the China Eastern Railway (Dong-qing Railway), which was completed in 1903. The railroad was a major joint Sino-Russo railroad system connecting Chita and Vladivostok in Russia, with a branch line connecting Harbin to the port of Lüshun. The railroad traversed northeastern China, and there was frequent movement of people and goods along its route.

Image below: China Eastern Railway

knitr::include_graphics("/Users/guanr./Desktop/railway.png")

In September 1910, the first cases of plague appeared in Russia. In October the Russian government deported Chinese workers suspected of being infected. These people arrived in the Chinese city of Manzhouli on the Sino-Russo border, the first stop on the Eastern Ching Railway in China. The plague spread rapidly along the railroad from the end of October and killed tens of thousands of people over the next three months. The Chinese government then dispatched the deputy supervisor of the Medical School of Army, Dr. Wu Lien-teh who was a Chinese specialist born in British Malaya and earned a doctorate in medicine at Cambridge University, to the northeast to take charge of the epidemic. With the support of the local government, Dr. Wu led many specialists to bring the pandemic under control by March of the following year, using strict restrictions on transportation, screening and isolation of suspected cases, and the promotion of his invention of cotton medical masks. Eventually Chinese government declared the end of the plague pandemic in April.

There have been a number of historians who have studied the pandemic and its context in considerable depth. Carol Benedict’s work examines bubonic plague in nineteenth-century China, noting that bubonic plague began to appear in southwestern China in the mid-nineteenth century (Benedict, 1996). As this region descended into turmoil in the 1850s-1870s, bubonic plague intensified and persisted there, becoming somewhat endemic. Soldiers suppressing rebellions in this region carried the pathogen elsewhere, and commercial activities also facilitated the spread of plague. Therefore, in the 1890s, many cases of plague appeared in Hong Kong, from where it spread throughout the world. In India, the plague pandemic of 1896-1898 killed tens of millions of people and was the culmination of the Third Plague Pandemic in human history, which lasted several decades.

William Summers’ book focuses on the Manchurian plague itself. He organizes the broad threads of events as they unfolded and highlights the role of geopolitics in this plague epidemic (Summers, 2012). Northeastern China was strongly influenced by Russia and Japan, and both Russia and Japan had established their own settlements and businesses there in an attempt to expand their control over this productive land. The Chinese government, meanwhile, was taking steps to secure its sovereignty over the region. All three parties were therefore using coercive anti-epidemic measures to expand and strengthen their presence.

Other scholars have noted the important role of the state in the pandemic. Du Hongli’s book clears up some of the details in greater depth and focuses on the role of Dr. Wu and his promotion of Western methods of epidemic prevention (Du, 2023). The Western methods were considered “scientific”, although in reality there were no scientific modern medicines to cure the plague and other pandemics: antibiotics were not invented and used until the 1940s. Thus, Western methods were primarily state-imposed pandemic-specific coercive measures. Of course, this kind of state coercion against pandemics was really a novelty in China’s history and only emerged at the beginning of the twentieth century. Du Lihong describes how such state-dominated mandatory measures were gradually accepted by some Chinese elites with the development of European imperialism in China, and some specific characteristics of the mandatory epidemic prevention in Manchuria, depending on the economic and social conditions of different areas. But in the broader context of geopolitical conflict, the matter of epidemic prevention became part of the nationalist discourse. The polemic about Western medicine or Chinese medicine has been going on since then and continues to exist. This is also the starting point for scholars such as Sean Lei to carry out their work on the modern development of Chinese medicine (Lei, 2014).

Past studies have not utilized digital humanities to present statistics from official reports on maps, even in a very simple way. This study primarily attempted to utilize the Report of Pandemic of the Eastern Three Provinces being published in 1911 (“1911 Report”) to present the data for each county on a map, and obtain historical geographic data and coordinates for each county were obtained through the World Historic Gazetteer. After obtaining the gazetteer, “.shp” files will be generated by ArcGIS Online. Ideally, the death case data for each county would be represented by the color and diameter of a circular icon, allowing the reader to see the geographic distribution of cases more visually.

Geography was very much a factor in the 1910-1911 Great Plague of Northeast China. This region was the birthplace of the Manchu rulers of the Qing Empire that was the last dynasty of imperial China, who were once semi-sedentary, semi-nomadic people living in a mixed farming-fishing-hunting economy. After the conquest of all of China in the mid-17th century, many Manchus and other native ethnic groups still lived in Manchuria. The population density here was much lower than China Proper, while the fertile black soil suitable for cultivation was vast. The Qing Empire prohibited the migration of peasants from China Proper to protect the environment of this birthplace. However, in response to the threat of Japan (which had by then colonized the Korean Peninsula) and Russia, which had already seized parts of China and was attempting to seize Manchuria, the Qing Empire greatly relaxed its restriction on immigration in the 1890s and began to encourage emigration in 1904. The influx of Chinese immigrants, China’s state building aiming to confront Russia and Japan, and the latter two’s attempts to control Manchuria shaped local geopolitics.

As a result, Manchuria was a veritable borderland at the time when great plague outbreak. It remained under the control of imperial and, later, republican China (until 1931), but Russian and Japanese imperialist expansion continued to exert increasing political, military, and economic influence in the region. The opening of the railroads also facilitated the development of a number of cities, such as Harbin, which was at the intersection of the main line of the China Eastern Railway and the branch line connecting the well-located Lüshun port. For Harbin’s crucial position in the railroad system and ensuing demographic and commercial flows, this city and its surrounding areas suffered the highest number of deaths in the plague pandemic. Geography further determined the administrative divisions and the medical statistics that followed. Manchuria was still in a state of administrative instability in 1910-1911, with many prefectures being created and then renamed or abolished, or a single prefecture later divided into two or more prefectures. This was due to the continued influx of population, disasters, and the development of transportation and trade.

This project relies on World Historical Gazetteer, a powerful and useful online database of place names. The general idea of its developers is that historians and researchers from various disciplines would be able to use the site to find out how the name of a particular place has changed throughout history. For some large cities, it is not difficult to figure out their former names, such as Tokyo, the capital of Japan, which was called Edo long before the mid-nineteenth century, and Ho Chi Minh City, the largest city in Vietnam, which was called Saigon until the triumph of the communist revolution. However, for smaller cities and towns, it is not so easy to know what they were called before. The World Historic Gazetteer can be of great help in this regard.

knitr::include_graphics("/Users/guanr./Desktop/WHG 1.png")

knitr::include_graphics("/Users/guanr./Desktop/WHG 2.png")

Moreover, one of core developers of WHG, Ruth Mostern, provides a very useful tutorial on Programming Historian, cooperating with Susan Grunewald. The tutorial teaches readers how to set up an electronic form and fill out it with raw data in order to upload it on WHG to create a dataset. Every row of data on the electronic form needs to have an ID and some identifying labels like place type and code, even though a simple Excel form if enough for collecting and classifying data. Therefore, the template form looks like this:

knitr::include_graphics("/Users/guanr./Desktop/WHG 3.png")

I used nine columns in my forms. ID, County, ModName, Latitude, Longitude, Source, AttestedDate, PlaceType, and CaseAmountc. So, my form looks like this:

knitr::include_graphics("/Users/guanr./Desktop/form 1.png")

By transferring the tables of the 1911 Report into electric form, I get a list of 69 counties. The next step is extracting data from WHG. However, in actual research, I found that the World Historic Gazetteer has a number of flaws that deserve to be discussed, and most of these are due to Manchuria’s unstable borders of administrative regions at that time and the incompatibility of the Latinization format of Chinese words.

The first common problem is the incompatibility caused by the spelling of the county’s Chinese name in Latin letters.There are several different formats to transcribe unique Chinese characters into the Latin alphabet, and the most influential of which are the Wade-Giles romanization and the modern Hanyu Pinyin format. The Wade-Giles romanization was invented in the mid-nineteenth century by a English official Thomas Wade and quickly became popular among the Europeans, and were suing as the dominant format from the late nineteenth century to the mid-twentieth century. Today its variant is still in use in Taiwan. Another format was invented in the mid-1950s, the Hanyu Pinyin format. The spelling rules of this format are quite different from those of the Wade-Giles romanization, but it has now become the standard spelling, including in academia. The problem is that much of the original data used for the World Historic Gazetteer spelled Chinese names in the Wade-Giles romanization, and many of the names do not contain the original Chinese characters. For the vast majority of current scholars, this poses a difficulty because they are not familiar with the Wade-Giles romanization. Searching for names in the Pinyin format sometimes yields no results.

Take for example the city of Manzhouli. This place was called Lubin County when the report was published in 1911. However, if a user search for Lubin in the WHG, you get no results.

knitr::include_graphics("/Users/guanr./Desktop/Lubin 1.png")

If you search in Chinese, either traditional or simplified Chinese characters, you also get no results. (Illustration)

knitr::include_graphics("/Users/guanr./Desktop/Lubin 2.png")

knitr::include_graphics("/Users/guanr./Desktop/Lubin 3.png")

The reason for this problem is that WHG only includes the Wetoma spelling of Lubin, and does not distinguish between the characters indicating the administrative level of the county and the name of the county. As a result, only a search for lu-pin-hsien brings up an entry for this this place. “Hsien” here is the Wetoma spelling of county and should not be joined with lu-pin using a hyphen. However, as in WHG, it is not possible to retrieve lu-pin; only lu-pin-hsien is searchable, because the three words are considered to be one single name. In addition, the modern name for this place, Manzhouli, has no corresponding Chinese character added, so a search for the name Manzhouli using Chinese characters would also come up empty.

knitr::include_graphics("/Users/guanr./Desktop/Lubin 4.png")

knitr::include_graphics("/Users/guanr./Desktop/Lubin 5.png")

This problem is not uncommon, especially for place names that are no longer in use today. Other examples are Yuqin County, Xincheng County, and Binjiang Ting. All three of these names are no longer in use. Yuqing County is now renamed Qing’an County, Xincheng County is renamed Fuyu County, and Binjiang Hall has been upgraded to Harbin City, a major city in northeastern China. Presumably because the names Yuqing, Xincheng, and Binjiang are no longer in use, WHG that created its database according to some older sources is using only the Witoma pinyin of the three old names. If one searches for their modern names, the location will still come up and basically the user will be able to find some of the names that the place used to have in the past in the variant column. But the problem is that most of the people who use this system want to search for names that are no longer in use today and then get the current name.

Another issue is the hierarchy of administrative divisions. At the time of the outbreak of the current plague pandemic, China was still under the rule of the Qing Empire, the last dynasty of imperial China. Back in 1910-1911, the main administrative hierarchy in China was provinces - prefectures/directly subordinate states - general states and counties. There were also more flexible halls: some were at the level of prefectures, while others were on the same level as counties or even lower. In official reports, prefectures, counties and halls are juxtaposed. In short, the administrative division of imperial China was quite complex. The problem caused by this complex zoning system in the unstable frontier of Manchuria was that the level of an administrative district could change considerably, with some states/prefectures becoming three counties today. Some halls have now become large cities. A more typical example of a county becoming multiple counties is Zhaozhou. In official reports, Zhaozhou is referred to as a prefecture. Today, however, it has been divided into three counties (cities): Zhaozhou, Zhaoyuan County and Zhaodong City. As a result, the boundaries of the administrative divisions have changed considerably. But this is not reflected in the whg. Zhaozhou is not mentioned below the entry for Zhaodong

knitr::include_graphics("/Users/guanr./Desktop/zhaodong.png")

There is also no mention of Zhaoyuan County or Zhaodong in the entry for Zhaozhou, and only the entry for Zhaoyuan County mentions Zhaozhou.

knitr::include_graphics("/Users/guanr./Desktop/zhaoyuan.png")

Of course, they all use the Wade-Giles format.

This is why using contemporary Chinese three-level administrative boundaries shp files on RStudio to create county boundaries is problematic. While constructing a plague Rmap with base map of prefectural/county boundaries is a worthwhile endeavor, it will be difficult to present the 1910-1911 Manchurian pandemic on a map until we figure out the administrative changes in the Manchurian region. In general, WHG needs to update its database, preferably to include a searchable option for the native language in which the place name is spoken. Perhaps adding a short text explaining the historical changes for each place names that has complex history is a solution.

A simple illustration of the death cases:

library(leaflet)
library(sf)     
## Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUE
library(dplyr)   
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(ggplot2)
setwd("/Users/guanr./Desktop/digital project/Guanran_RMap/1911_General_Cases")
General_Cases <- st_read("~/Desktop/digital project/Guanran_RMap/1911_General_Cases/1911_General_Cases.shp")
## Reading layer `1911_General_Cases' from data source 
##   `/Users/guanr./Desktop/digital project/Guanran_RMap/1911_General_Cases/1911_General_Cases.shp' 
##   using driver `ESRI Shapefile'
## Simple feature collection with 69 features and 5 fields
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: 13072620 ymin: 4736006 xmax: 14550900 ymax: 6377289
## Projected CRS: WGS 84 / Pseudo-Mercator
plot(General_Cases['CaseAmount'])