epidiomiological diffusion processes in war

8/12/2019 Epidiomiological Diffusion Processes in War

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70 M. SMALLMAN-RAYNOR AND A. D. CLIFF

classic book, Epidemics Resulting From Wars, Friedrich Prinzing notes that the French

Army lost 1015 per cent of its effective strength to morbidity and mortality from

cholera in the first year of the Crimean War (18546). [3] A similar proportion of the

Prussian Army succumbed to cholera in the AustroPrussian War of 1866.[4] But the

highest death tolls are usually associated with the spread of cholera among civilian

populations, often in the immediate aftermath of war. The cholera epidemic that

struck the Philippine Islands between 1902 and 1904 began just as the three-year war

(18991902) against American annexation was drawing to a close. The war had already

claimed up to 800 000 Filipino lives, and this in a population of less than eight million.

The cholera epidemic that followed the war spread across the archipelago and left

another 200 000 dead.[5]

Despite the historical association of cholera and war, geographical studies of the

disease have tended to focus on epidemic spread in peacetime. [6] As a consequence,

relatively little is known of the diffusion of cholera as a sequel to armed conflict. To

redress this imbalance, we present here a geographical analysis of the cholera epidemic

which followed in the wake of the PhilippineAmerican War. The social and political

context of this epidemic has been outlined in a number of recent studies. [7] In this paper,

we add a spatial dimension by examining the processes by which the epidemic diffused

on different geographical levels in the course of its first year, March 1902February

1903. To these ends, we make use of a novel archival source in epidemiological studies:

the sanitary dispatches prepared by the Chief Quarantine Officer for the Philippine

Islands and reprinted in the US Public Health Services Public Health Reports.[8] For

the period covered by this paper, the post of Chief Quarantine Officer was held by J. C.

Perry, a Passed Assistant Surgeon of the US Marine Hospital Service;[9] we examine

Perrys textual accounts and numerical summaries of the cholera epidemic in subsequentsections.

The present study is part of an ongoing project concerned with the use of island

communities as laboratories for disease diffusion analyses.[10] We begin with a brief

description of the Philippine Islands, the nature of cholera and the wartime legacies

that influenced its spread. In the second part, we outline the nature and sources of the

cholera data contained in the Public Health Reports. Then, we use qualitative evidence

contained in the Reports to reconstruct the routes by which cholera diffused through

the Philippines archipelago. Finally, we turn to the quantitative evidence contained in

the Reports to identify the diffusion processes operating at the geographical scales of

nation, island and province.

Background to the epidemic

The study site

The Philippines archipelago consists of some 7100 islands strewn over half a million

square miles of ocean (Figure 1). At about the time of the epidemic, in 1903, some five

per cent of the islands were inhabited by a population totalling 7 635 000. [11] Almost

half resided on the northern island of Luzo

n; only seven other islands (Bohol, Cebu

,

Leyte, Mindanao, Negros, Panay and Sa

mar) recorded populations in excess of 100 000.

Manila City, situated on the west coast of Luzo

n, was the largest settlement (1903

population 220 000), chief port and trading centre. Elsewhere, the settlement pattern

was characterized by scattered villages and towns of less than 40 000 inhabitants. [12]

As a country of oceanic islands, settlements in the Philippines were doubly isolated
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71DIFFUSION PROCESSES AND WAR IN THE PHILIPPINES

Figure 1. The Philippine Islands.

externally from the rest of the world, and internally from each other. Internal isolation

was not only by way of the sea, from one island to another, but also, because of the

rugged and mountainous nature of much of the terrain, from settlement to settlement

on a single island.[13] The profound epidemiological consequences of such isolation have

been reviewed at length elsewhere[14] but, in essence, natural isolation served as an

effective barrier to the spread of infectious diseases.

The war context

The PhilippineAmerican War gravely impaired the epidemiological protection afforded

by natural isolation. Contributory factors have been outlined in other sources.[15]

The


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war began on 4 February 1899 and officially ended some 40 months later in July 1902.

During this period, over 100 000 US troops were deployed to combat the rural guerrilla

forces. Many of the troops were stationed in an interconnected network of some 500

garrison towns, and these towns became the focus for migrants seeking protection from

the war in the countryside. Large-scale population movements and congregation were

further fuelled by agricultural dislocation, the disruption of food supply lines and the

US strategy of forced population concentration to combat the guerrilla fighting. Thus,

when cholera appeared in the archipelago in the penultimate month of fighting, March

1902, the isolation of many settlements had been eroded by three years of military

occupation, conflict, population displacement and congregation. The situation was

compounded by population dispersal in the immediate aftermath of the war.

Recent histories of the 19024 cholera epidemic on the Philippine Islands have

ascribed only a limited role to American military personnel in the carriage of thedisease.[16] A number of American soldiers were certainly afflicted in the early stages of

the epidemic, although instances in which they were directly implicated in the spread

of cholera are few.[17] Troopships, in particular, were a potentially efficient mechanism

for the carriage of the disease from port to port. But, with one critical exception in the

very early stages of the epidemic, quarantine appears to have contained the spread of

cholera by this route.[18]

Rather, the influence of war on the spread of cholera rested with the social and

environmental conditions created by the hostilities[19] and the military-style approach

to disease control.[20] The social and environmental aftermath of the PhilippineAmerican

War is well illustrated by the experience of the provinces of Batangas and La Laguna,

Luzo

n Island[21] (Figure 1). Batangas and La Laguna had been the scene of intense

fighting during the war and, as late as December 1901, population reconcentration wasundertaken by the American administration as part of its strategy finally to quash the

rebel insurgents. Such were the cramped and unsanitary conditions endured by the

reconcentrated populations that, by April 1902, dysentery and malaria were rife. Health

problems were exacerbated by food shortages which were, in large measure, attributable

to the destruction of local agricultural infrastructure earlier in the war. Thus, when

cholera reached Batangas and La Laguna in late April 1902, it spread rapidly through

the dense, unsanitary and physically weakened populations. The significance of these

conditions was not lost on contemporary observers; one US military report attributed

the very high cholera mortality in the two provinces to the demoralising and debilitating

influences of war.[22] Moreover, food shortages fuelled an illicit movement of people

and produce that military restrictions and quarantine cordons were powerless to stop.

These local population movements gave rise to some well-documented episodes in the

diffusion of the epidemic[23] and, doubtless, countless others.

The nature of cholera

Classic Asiatic cholera which caused the epidemic is a severe, often rapidly fatal, disease

produced by the bacterium, vibrio cholerae. Transmission of the bacterium usually

occurs via the ingestion of faecally contaminated water and, less commonly, food. As

regards its clinical course, an incubation period of two to five days is usually followed

by the sudden onset of diarrhoea and vomiting, giving rise to massive fluid loss and

dehydration. Consequent symptoms include cramps, a reduction in body temperature

and blood pressure leading to shock and, ultimately, death within a few hours or days

of symptom onset. Mortality is typically witnessed in 4060 per cent of untreated

cases.[24]


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At least until the beginning of the present century, the Philippine Islands lacked the

conditions necessary to maintain cholera in endemic form. So, for each of the six

epidemics to strike the country by 1904, first in 1820 and then in the 1840s, 1860s,

twice in the 1880s and finally in 1902, an external source of the vibrio is either known

or strongly suspected.[25] As a consequence, each epidemic had a discrete and definable

starting point in the archipelago and each event was separated by an extended disease-

free period.[26]

The data

Sources of data

One legacy of the American annexation of the Philippine Islands is the detailed sanitary

reports from the period. Officers of the United States Public Health Service (USPHS),

stationed in the Philippines, were directed to submit reports of the progress of the

cholera epidemic to the USPHS Surgeon-General in Washington, DC. These reports

were published in the weekly Public Health Reports, the US equivalent of England and

Wales Weekly Returns of the Registrar-General.[27] The information contained in the

Public Health Reports forms part of the original material on which the annual reports

of the Chief Quarantine Officer for the Philippine Islands, published in the widely used

Annual Report of the Philippines Commission, were based.[28] In this paper, we use the

epidemiological information contained in the weekly volumes of the Public Health

Reports to reconstruct the spread of the epidemic. These data are supplemented by

demographic information from the 1903 Census of the Philippine Islands.[29]

For the purposes of enumeration under the 1903 census, the Philippines was organizedinto some 1000 municipalities.[30] Municipalities were commensurate with settlements

and ranged in size from small villages to large towns. Each municipality was allocated

to one of 51 provinces or comandancias (military districts) and these, in turn, to the

major island groupings of the Philippines archipelago.[31] All epidemiological information

included in thePublic Health Reportsis coded according to these standard geographical

divisions of municipality, province/comandanciaand island.

It is convenient to divide the information in the Public Health Reports into two

categories: numerical evidence; and textual accounts.

Numerical evidence. The cholera epidemic began on, or about, 20 March 1902 and

persisted for 99 weeks until the beginning of February 1904. For each of these 99

weeks, the Public Health Reports record the number of cholera cases and deaths

registered in infected municipalities.Textual accounts. The numerical reports of morbidity and mortality were usually

accompanied by textual accounts of the development of the epidemic. These were

prepared by the Chief Quarantine Officer for the Philippines from reports filed by US

officials in the various provinces. The accounts contain details of the factors that

influenced the size and severity of the epidemic, and measures adopted to combat its

spread. In addition, and crucially from a geographical point of view, the accounts

record the geographical source of cholera in various locations.

Selection of time period

The textual accounts of the 19024 cholera epidemic describe how it passed through

the Philippine Islands as two temporally distinct, but spatially concordant, waves of


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9000

0

1Week

Ch

oleraincidence

5000

8000

7000

6000

4000

3000

2000

1000

50 61 99

Wave I (weeks 150) Wave II (weeks 6199)

Figure 2. National series of cholera cases (histograms) and deaths (line traces) by week, PhilippineIslands, March 1902February 1903. The series are based on the weekly counts of morbidityand mortality recorded in the Public Health Reportsfor 570 infected municipalities. The horizontalaxis has been formed by coding the first week of the epidemic (ending 22 March 1902) week 1,with subsequent weeks numbered sequentially thereafter up to, and including, week 99 (ending6 February 1904). The graph defines two waves of infection; summary details of each wave are

given in Table 1. The present analysis is restricted to the diffusion of wave I (weeks 150).

T1Summary details of infection Waves I and II associated with the 19024 cholera epidemic in the

Philippine Islands

Wave 1 Wave 2

Start 22 March 1902 (week 1) 16 May 1903 (week 61)End 28 February 1903 (week 50) 6 February 1904 (week 99)

Duration (weeks) 50 39Cases 71 221 26 267Deaths 47 548 19 896

Epidemic peak 4 October 1902 (week 29) 22 August 1903 (week 75)

Date given as the last day of the calendar week. The week number, coded sequentially from the firstweek of the epidemic (22 March 1902, week 1), is given in parentheses. Epidemic peak is defined as the week in which the maximum number of cases was reported, with thedate given here as the last day of that calendar week.

infection. Figure 2, which is based on the numerical information contained in thePublic

Health Reports, plots the national series of cholera morbidity and mortality on a weekly

basis, March 1902February 1904.[32]

The two infection waves identified in Figure 2 formed discrete diffusion events.[33] As

Table 1 shows, wave I began in the third week of March 1902 (week 1) and persisted

for 50 weeks, ending in the last week of February 1903 (week 50). It reached a peak


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in early October (week 29) and was associated with a reported total of 71 221 cases

and 47 548 deaths. The rather less severe wave II began in late May 1903 (week 61),

lasted 39 weeks to early February 1904 (week 99) and is documented to have claimed

some 20 000 lives. In this paper, we analyse the diffusion of the more severe wave I.

The diffusion of wave II is examined elsewhere.[34]

Database formation

The numerical and textual information contained in the Public Health Reports was

used to form two databases relating to the occurrence of wave I:

Database 1: numerical evidence. The number of infected municipalities documented in

the Public Health Reports varies on a weekly basis, but a total of n=441 different

municipalities (including Manila City) were included at some stage during the t=50weeks duration of wave I.[35] These municipalities were located in 39 provinces on 13

islands; the assignment of municipalities to provinces and islands is shown in Table

2.[36] For each infected municipality, the weekly disease counts were abstracted to form

(44150) spacetime matrices of (1) cholera morbidity, and (2) cholera mortality.

Furthern50 matrices, at the spatial levels of province and island, were then formed

by dividing the 44150 matrices into the constituent municipalities of individual

provinces and islands. The total number of cases and deaths recorded nationally, and

by island and province, is shown in Table 2.

Database 2: textual accounts. All information on inter-area linkages in the spread of

cholera was abstracted from the Public Health Reports, and organized to form a time-

sequenced account of the diffusion of wave I.

First the textual accounts in database 2 are used to reconstruct the broad routes bywhich wave I spread through the archipelago. We then turn to the numerical evidence

in database 1 to examine the processes by which the wave spread at the geographical

levels of province, island and nation.

Textual accounts: reconstruction of national diffusion routes

In a period of less than 12 months, wave I of the cholera epidemic (March 1902February

1903) had been introduced to the Philippines, spread hundreds of kilometres from its

point of introduction to reach the most remote islands of the archipelago, and faded

away.

A telegram dated 24 March 1902 provided the first evidence of cholera in the islands.

The informant was the Chief Quarantine Officer for the Philippines, J. C. Perry, and

the message was unequivocal: Cholera is now present at Manila; 18 cases.[37] In fact,the first cases had appeared a few days earlier, on 20 March, in the Farola district of

the city.[38] It is unlikely that the ultimate source of cholera in Manila will ever be

known, although contemporary accounts speculated on its importation with fresh

vegetables from Canton, China, where cholera had been present for some time.[39]

Whatever the source of the disease, emergency measures were immediately invoked

in the city. Public health surveillance was intensified, all suspicious cases were admitted

to hospital, contacts were sent to the citys detention camp, infected houses were

cleansed and placed under guard, all green vegetables were destroyed, wells and cisterns

were closed and distilled water stations established. To prevent onwards spread from

Manila to the provinces, a cordon was thrown around the city; ferry boat and rail

traffic was halted and a permit system was introduced to control the movements of

individuals.[40]


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T 2Number of cholera cases and deaths recorded by island and province in the Public Health Reports

for wave I of the epidemic, 22 March 190228 February 1903

Island Province Number of Cases Deathsmunicipalities

Basilan Basilan 1 0 (000) 3 (2253)Bohol Bohol 11 1911 (7098) 1274 (4732)Cebu

Cebu

18 2288 (3500) 1323 (2024)

Leyte Leyte 9 569 (1463) 396 (1018)Luzo

n 264 30 271 (8411) 22 517 (6257)

Albay 2 264 (1103) 190 (794)Bataa

n 8 1204 (26657) 861 (19063)

Batangas 14 3080 (11951) 2527 (9805)Benguet 1 4 (4362) 2 (2181)Bulacaa

n 22 1427 (6390) 960 (4299)

Cagaya

n 2 50 (350) 33 (231)Camarines 23 1490 (6382) 1041 (4459)Cavite 14 884 (6559) 606 (4496)Ilocos Norte 1 360 (2036) 279 (1578)Ilocos Sur 16 1306 (7514) 864 (4971)Isabela 1 24 (344) 14 (201)La Laguna 23 2619 (17624) 2227 (14986)La Unio

n 13 3661 (28649) 2819 (22060)

Manila 1 4621 (21011) 3487 (15855)Nueva E

cija 17 1346 (10120) 1119 (8414)

Pampanga 21 1044 (4689) 753 (3382)Pangasina

n 30 4163 (10552) 3036 (7696)

Rizal 17 715 (4815) 470 (3165)Sorsogo

n 3 225 (1868) 87 (722)

Ta

rlac 8 312 (2337) 217 (1625)Tayabas 9 223 (1484) 170 (1131)Zambales 18 1249 (12320) 755 (7447)

Marinduque Marinduque 2 246 (4761) 168 (3251)Masbate Masbate 4 188 (4305) 116 (2656)Mindanao 20 2271 (8890) 1137 (4451)

Misamis 18 1883 (13899) 953 (7035)Surigao 1 198 (1994) 86 (866)Zamboanga 1 190 (9182) 98 (4736)

Mindoro Mindoro 4 283 (8757) 262 (8107)Negros 30 5011 (10257) 3328 (6814)

Negros 20 4212 (13871) 2694 (8872)Occidental

Negros Oriental 10 799 (4322) 634 (3429)Panay 72 27 713 (35068) 16 691 (21121)

Antique 12 782 (5958) 538 (4099)Ca

piz 23 2984 (11698) 1937 (7593)

Ilolo 37 23 947 (59285) 14 216 (35194)

Romblo

n Romblo

n 1 200 (3784) 74 (1400)Sa

mar Sa

mar 5 270 (1017) 259 (975)

Total 441 71 221 (9327) 47 548 (6227)

Rates per 10 000 population (1903 census) are shown in parentheses. Sub-province of Tayabas.


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Manila, 20 March 1902Orion, 19 April 1902Hagonoy, 19 April 1902Nueva Caceres, 19 April 1902Calamba, 19 April 1902Binan, 26 April 1902Santa Cruz, 3 May 1902Tacloban, 10 May 1902Batangas, 17 May 1902Tayabas 17 May 1902Pangasinan 24 May 1902Sumar, 31 May June 1902Calapan, 14 June 1902Carigara, 28 June 1902Boac, 5 July 1902Cebu, 12 July 1902Catmon, 23 August 1902Iloilo, 23 August 1902Surigao, 16 September 1902

Misamis, 31 January 1903Tobogan

3

11

ChinaSea

PacificOcean

12345678910111213141516171819

2021

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2

67

5

13

9

15

104

182117

16

14

12

8

19

20

''

'

'

'

~

'

Figure 3. Diffusion of wave I of the cholera epidemic, Philippine Islands, March 1902February1903. The reconstruction is based on the textual accounts of the Chief Quarantine Officer forthe Philippine Islands. Vectors show the spatial links in the transmission of cholera; the date andtime of appearance of cholera in various municipalities and provinces is indicated. Source:Public

Health Reports.

By mid-April it had become evident that these efforts to quarantine Manila from the

rest of the archipelago had failed (Figure 3). The dispatches from the Chief Quarantine

Officer recount how the disease was first carried to two towns on Manila Bay, Orio

n

and Hagonoy, by escapees aboard local bancas (a type of native sailing vessel).[41]

Further localized spread from Manila occurred down the Pasig River and into lake

Laguna de Bay, with the lakeside towns of Calamba, Bin

an and Santa Cruz infected

by early May. From La Laguna province, the bacterium spread overland to Batangas

with onwards carriage to Calapa

n on the adjacent island of Mindoro.[42]

From Mindoro,


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the bacterium was carried by bancato the island of Marinduque in July. [43] Meanwhile,

northwards spread from Manila occurred along the Pangasina

n railway, eventually

reaching La Unio

n province by June.[44]

To set against this contagious wave-like expansion outwards from Manila, as early

as April 1902 we obtain the first impression of long-distance carriage of the bacterium

by the United States Army. A dispatch from the Chief Quarantine Officer recounts

how a troopship, headed from Manila, carried the bacterium to the port city of Nueva

Ca

ceres, south-eastern Luzo

n, in mid-April.[45] This establishment of Nueva Ca

ceres as

an epidemic bridgehead was to play a pivotal role in the subsequent appearance of the

disease in the southern islands. By early May, the bacterium had appeared in Tacloban,

Leyte Island, with Nueva Ca

ceres the suspected source.[46] From here, the disease spread

rapidly to the adjacent islands, the arrival of the disease in the island of Cebu

in August

1902 having been documented in particular detail:

a banca arrived at Tobogan (sic.), on this island [Cebu

], with a dead Filipino on boardfrom Carigara, Leyte, and requested permission to enter that port and to inter the deadman. This was refused by the presidente. . . . [T]he banca had gone, after this refusal,to Catmo

`n, where it was allowed to land and the body buried. Following this, within

a few days (the exact time not known), several cases of death occurred preceded byvomiting and diarrhea.[47]

Although no source is reported for Negros Island, some link to the outbreak in the

adjacent Cebu

must be suspected. But, once in Negros, the disease spread by native

sailing vessel to the populous island of Panay by late August 1902 [48] and Misamis

province on the far southern island of Mindanao by January of the following year. [49]

Numerical evidence: diffusion processes at different spatial scales

The textual record takes us thus far in unravelling the diffusion of wave I. In this

section, we turn to the numerical evidence in database 1 to see what further information

about the diffusion process can be gleaned from it. The analysis begins with a comment

on the quality of the numerical evidence contained in the Public Health Reports. Then,

after a brief review of diffusion processes, complementary statistical techniques are

applied to identify the manner in which cholera spread on the spatial levels of nation,

island and province.

Data completeness. Some idea of the completeness of the statistical data included in

the Public Health Reports can be gained from the reports of J. C. Perry, the ChiefQuarantine Officer. For example, in his dispatch of 2 August 1902, Perry estimated the

reporting completeness for cholera at 80 per cent.[50] Six weeks later, he revised his

estimate down to 70 per cent, only to raise it to 75 per cent at the end of the year. [51]

Certainly, the dispatches recount the logistical difficulties encountered in the surveillance

programme, particularly in the provinces. For example, the breakdown in tele-

communications between Manila and the rest of the archipelago in the early weeks of

November 1902 prompted Perry to warn that the reported data was . . . not a true

index of the prevalence of cholera outside of Manila.[52]

Rather less optimistic estimates of statistical completeness are gained when the data

in the Public Health Reports are compared with mortality counts included in Volume

III of the 1903 census. The latter source registered a national total of 137 505 cholera

deaths for the year 1902.[53]

A total of 45 625 cholera deaths were recorded in the Public


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Health Reports for the same period, representing a statistical completeness of about 33

per cent for cholera mortality.

Because of these uncertainties about the accuracy of the absolute disease counts, the

n50 spacetime matrices in database 1 were reduced to a binary basis, recording 1 if

a case or death occurred at a given spacetime location and 0 otherwise. All the analysis

described in this paper is based on these binary matrices of disease presence/absence.

Diffusion processes. Accounts of the spread of an infectious disease usually recognize

three main types of diffusion process.[54] Acontagious process describes the situation in

which the disease moves from its centre of introduction to its physically nearest

neighbouring centres. These, in their turn, transmit the disease to their geographically

nearest neighbours, and so on. In this manner, the disease spreads in a wave-like

manner outwards from its point of introduction. Alternatively, a hierarchicalprocess

describes the situation in which the disease moves progressively through the urban

hierarchy. Typically, the initial point of introduction of a disease is the largest urban

centre. Then, urban centres next in size follow, and so on, through to the smallest

settlements. Finally, amixedprocess describes the situation in which the spread pattern

contains components of both contagious and hierarchical diffusion.

A number of methods have been developed for the identification and analysis of

these diffusion processes.[55] In this paper, two complementary statistical methods

are applied to the Philippines data: (1) multiple regression analysis; and (2) spatial

autocorrelation.

Regression analysis: diffusion patterns in space

Method. In this approach, the time-ordered sequence of appearance of a disease in

the settlements of an urban system is modelled as a function of: (1) urban population

size, representing the hierarchical component in the spread process; and (2) geographical

distance from the settlement of initial introduction, representing the contagious com-

ponent.[56] Specifically, for a given geographical area of the Philippines (nation, island

or province), the first week in which cholera was recorded is coded as week 1, and for

municipality i, the week in which the disease was first reported in that municipality is

coded as week 2, or 3, or 4, etc. This week is denoted as ti. Then, the regression model

loge(ti)=b0+biloge(Pi)+b2loge(di)+ei (1)

was postulated. Here, Pi is the population of municipality i in 1903, di is the straight-line

distance (in kilometres) of that municipality from the municipality in which cholera wasfirst reported and e iis an error term. For many areas of the Philippines, the independent

variables, Pianddi, can be shown to display a double-logarithmic relationship with ti; the

logarithmic transformations in equation (1) serve to linearize these.

The regression model in equation (1) was fitted to each of the n (municipality)50

(weeks) spacetime matrices of cholera morbidity at the spatial levels of nation, island

and province. Model fitting was by ordinary least squares using a stepwise algorithm.

Because of the small sample sizes (less than eight infected municipalities) in some

provinces and islands, analysis was restricted to 32 areas (24 provinces, seven islands

and the nation). Where more than one municipality was recorded as the point of

introduction for a given area,diwas estimated as the average distanced

iof municipality

i from the introduction points. Finally, one potential complication in the regression

procedure is possible co-linearity between population size and distance. In particular,


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11

4.0

1.06

Loge(population)

3.0

2.0

(b)

6

4.0

1.01

Loge(distance)

Loge

(time) 3.0

2.0

(a)

Figure 4. Spread processes on the national level, cholera wave I. (a) Relationship between thetime of first appearance of cholera in each of 440 municipalities and distance from epidemicorigin. (b)Relationship between the date of first appearance of cholerain each of 440 municipalitiesand population size. All variables have been logarithmically transformed. Superimposed on each

graph is a trend line fitted to the data by ordinary least squares.

a decrease in municipality size with increasing distance would hinder separation of the

contagious and hierarchical components in the model. Consequently, Pearsons r

correlation coefficient was used to assess the level of correlation between the independent

variables in each model.

Results. The application of regression analysis to the diffusion problem is illustrated

graphically for the Philippine Islands as a whole in Figure 4, although the indexsettlement (Manila) has been omitted. A striking feature of Figure 4 is the positive

association between distance and time to infection [Fig. 4(a)]. Generally, municipalities

proximal to the point of introduction of cholera (Manila) were infected first, with more

distant centres infected at increasingly later dates. Such a pattern accords with the

operation of a spatially contagious component in the diffusion process. However, only

very weak evidence exists for the operation of a hierarchical component [Fig. 4(b)].

Under this process, an inverse association between the {log e(Pi)} and the {loge(ti)} (that

is, the larger the municipality, the shorter the time to infection) would be expected.

The low association is indicated by the near-horizontal regression line in Figure 4(b).

Table 3 examines the spread process using the framework of the multiple regression

model defined in equation (1).

National level. Model 1 shows that time to infection is positively associated with thedistance variable and negatively associated with the population variable; although just

statistically significant, the low and positive correlation (rPd=+014; 95 per cent

confidence interval +005 to +023) between the independent variables suggests that

the modelling procedure was reasonably successful in separating the hierarchical and

contagious components. As would be expected from the simple regressions in Figure

4, however, the relative importance of the distance variable is underscored by its entry

in step 1 of the model. Taken together, these results indicate that wave I of the cholera

epidemic spread through the archipelago as a mixed diffusion process with a dominant

contagious component.

Islands and provinces Models 232 in Table 3 summarize the results of the analysis at

the finer geographical levels of island and province. For each model, only those


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independent variables which made a statistically significant contribution to the model

are shown. In some areas, one or more municipalities served as extreme outliers that

influenced the parameters of the regression model. All results relate to models with

extreme outliers omitted; these are indicated in Table 3.

The most striking feature of models 232 is the importance they attach to the distance

variable. All seven islands and two-thirds of the provinces display a positive association

between loge(ti) and loge(di). The distance variable was entered as step 1 in 23 areas

(seven islands and 16 provinces) and formed the sole significant regressor in 19 models

(six islands and 13 provinces). Only eight areas (one island and seven provinces) displayed

a negative association between loge(ti) and loge(Pi), with the population variable entered

as step 1 in just three models. Both independent variables failed to make a significant

contribution to five models. Finally, it is noteworthy that only two areas displayed

evidence of a statistically significant correlation between the independent variables.These results confirm the importance of a distance-dominated diffusion process in

many geographical areas and on all spatial scales. Three-quarters of the areas displayed

either a purely contagious process (six islands and 13 provinces) or a mixed process

with a dominant contagious element (one island, three provinces and the nation). Only

three areas (provinces) displayed a purely hierarchical process.

Rank size rule. The structure of an urban system may influence the type of transmission

process in operation.[57] In particular, the operation of a hierarchical diffusion process

is, inter alia, dependent on a well-developed settlement hierarchy.[58] It is instructive,

therefore, to examine the results of the regression analysis in Table 3 in the context of

urban size structure via the ranksize rule.[59] Let Pk be the population of the kth

municipality in the series k=1, 2, 3, . . .,n in which all municipalities are arranged in

descending order by population. Then, the ranksize rule can be written as

log(Pk)=log01(logk)+ek (2)

where 0 and 1 are constants to be estimated and ek is an error term. Full details of

the model are given elsewhere,[60] but larger (negative) values of2mark larger (relative)

differences in municipality size.

Equation (2) was fitted to each area in Table 3 by ordinary least squares. Because

of the complications encountered in the fitting of the ranksize rule to the lower limb

of the size hierarchy,[61] analysis was restricted to municipalities with populations in

excess of the national average municipality size (that is, 6846 in 1903).

An expectation of the ranksize analysis is that large (negative) values of1, which

identify more pronounced differences in urban size structure, are more likely to be

associated with the operation of a hierarchical diffusion process. Conversely, low values

of1 mark less pronounced differences in size structure and therefore are less likely to

be associated with a hierarchical diffusion process. The results of the present analysis

confirm this expectation. As Table 3 shows, the largest (negative) values of1(less than

05) are found in the three areas (Batangas, La Laguna and Rizal provinces) for

which a purely hierarchical diffusion process was identified. Moreover, when areas are

grouped by diffusion process, the average values of1(that is,

1) reduce systematically

from 064 (purely hierarchical) to 038 (mixed contagioushierarchical) and to

035 (purely contagious).

Spatial autocorrelation analysis: diffusion patterns in time

Although regression analysis provides an insight into the processes by which cholera

first spread to each municipality in a given area, an alternative approach is required


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to determine the changing role of contagious and hierarchical components as the

epidemic unfolded over time. One way to assess this temporal variability is by the

application of spatial autocorrelation analysis.

Method. The application of spatial autocorrelation analysis to epidemiological diffusion

studies is described by Cliffet al.[62] In brief, the area of the Philippines (province, island

and nation) over which the spread is occurring is treated as a graph consisting of a set

of nodes (municipalities) and the links between them. These links can be formed to

give a graph which corresponds closely to a hypothetical diffusion process. For the

purposes of the present analysis, each of the 32 areas (the nation, seven islands, 24

provinces) in Table 3 was reduced to two graphs.

(1) Minimum spanning tree (MST).[63]

This defines the area such that all municipalitiesare joined to their geographically nearest neighbouring municipalities. This network

implies a highly localized, contagious, spread process.

(2) Urban population hierarchy. This defines the area such that all municipalities are

joined to their next largest, and next smallest, municipalities in terms of the rank

order of the population size in 1903. This network implies a strict hierarchical

diffusion process.

To discriminate between the two graphs, for each of the 32 geographical areas a

binary outbreak/no outbreak map was drawn for each of the 50 weekly periods of

the epidemic. Vertices (municipalities) on each graph so defined were coded black (B)

for cases of cholera or white (W) for no cases, and the BW join-count statistic under

non-free sampling was computed for each to measure the degree of contagion present. [64]

The BWstatistic is defined as

BW=12

n

n=1

n

n=1

wij(xixj)2 (3)

irj

wherew ij=1 if a link existed between the vertices iand jon the graph in question and

wij=0 otherwise; xi=1 if vertexiwas colour-coded Band x i=0 if the vertex was coded

W. In the present analysis, the sampling distribution ofBWunder the null hypothesis

of no contagion in outbreaks was assumed to be normally distributed for graphs with

20 or more vertices; BWmay be tested for significant departure from its null value as

a standardized normal (z) score.[65] This standardized score marks the degree of

correspondence between any graph and the transmission path followed by the diffusionwave: the larger (negative) the standardized score forBW, the greater the correspondence

between the hypothetical and the actual diffusion paths. For graphs with less than 20

vertices, the approximation for BWjoins described in Cliffand Ord was applied.[66]

Results. The national level results are illustrated in Figure 5. Figure 5(a) plots the

weekly number of cholera cases recorded; the vertical peaked line drawn at week 29

marks the peak week of the infection wave. Figure 5(b) and (c) give the autocorrelation

results in the corresponding weeks of the epidemic for the MST graph and the hierarchy

graph, respectively. For each weekly period, the vertical axes plot the z-scores [x (1)

for plotting convenience] evaluated for the BWstatistic of equation (3). Note that, due

to the confinement of cholera to Manila during the first four weeks of the observation

period, the results are illustrated for weeks 550 only. The horizontal lines drawn at


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5

05

Week

z(x-1)

10

1.65

15 20 25 30 35 40 45 50

(c)

7

2

z(x-1)

1

(b)

10 000

0

Cases

2000

(a)

4000

6000

8000

0

1

2

3

4

5

6

1.65

Pre-peak Post-peak

Figure 5. Join-count statistics for cholera diffusion at the national level, Philippine Islands. (a)Weekly count of cholera cases, weeks 550. The remaining charts plot weekly values of the BW

join-count statistic as a z-score (x1, for convenience in plotting) on a minimum spanning tree(MST) graph (b) and an urban population hierarchy graph (c). The solid horizontal line at z=165 marks the P=005 significance level in a one-tailed test for positive spatial autocorrelation;statistically significant scores are identifed by the shaded bars. For reference, the vertical dashed

line marks the peak week of the epidemic.

z=1.65 mark statistically significant standard. Normal deviates (=0.05 level, one-tailed test); bars above this value have been shaded. Figure 5(b) shows that the MST

graph is important throughout the course of the infection wave; strong and positive

spatial autocorrelation is recorded for 41 of the 46 weekly periods. Although a reduction

in z-scores can be identified over time (indicative of a weakening in the contagious

component during the course of the infection wave), scores remain very high until week

50. In contrast, Figure 5(c) shows that the urban hierarchy graph is important for only

a seven-week period leading to the epidemic peak. These findings suggest a transmission

process which started through localized spread to nearest neighbour settlements. This

contagious process was bolstered by hierarchical spread as the epidemic developed to

its peak, reverting to a purely contagious process during epidemic fade-out. Such an

interpretation accords with the mixed diffusion process identified by multiple regression

analysis in model 1 of Table 3.


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0

14

0

10

Pre-peak

NumberofsignificantBWscores

8

2

6 4 2 4 6 82

(d)

10

Post-peak

4

6

8

10

12

14

0NumberofsignificantBWscores

2

(a)

4

6

8

10

12

14


2

(b)

4

6

8

10

12

14


2

(c)

4

6

8

10

12

010

Pre-peak

8 6 4 2 4 6 82 10

Post-peak

Figure 6. Join-count statistics for cholera diffusion at the levels of province and island, PhilippineIslands. The charts plot the number of times a significant BW statistic was obtained for variousweekly periods. The results are shown at the p=01 significance level (bars) and the p=005significance level (line trace) in a one-tailed test for positive spatial autocorrelation. (a) Minimumspanning tree (MST) graph, provinces. (b) Urban population hierarchy graph, provinces. (c)MST graph, islands. (d) Urban population hierarchy graph, islands. Vertical pecked lines indicateepidemic peaks, denoted at week 0 on the horizontal axis. The time scale on the horizontal axesis in weeks either side of the epidemic peaks. The maximum possible scores in a given week are

24 for provinces in (a) and (b) and seven for islands in (c) and (d).

Islands and provinces. As judged by the number of significant counts in Figure 6, the

spatial levels of province and island have three features in common:

(1) from the start of each local epidemic wave until shortly after the peak week,

spatially contagious spread was more important than hierarchical spread;

(2) contagious spread was most important around the peak week;

(3) hierarchical spread was generally most important from two or three weeks before

epidemic peaks to six or seven weeks after.

These island and province findings are broadly similar to those for the national level

illustrated in Figure 5; at these scales, the transmission process also started as localized

spread among nearest neighbour settlements, and this contagious spread was joined by

a hierarchical component in the immediate build-up to epidemic peaks. However, unlike

the national spread process, there is no evidence of reversion to purely contagious spread

in the fade-out phase of the epidemic. Finally, Figure 6 also shows that diffusion patterns

were much more strongly developed at the provincial- than the island-level scale.


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war (the second US cholera epidemic occurred immediately after the War Between

the States), we may hypothesize, given the analyses presented in this paper, that

war may not materially alter the geographical engines driving diffusion processes,

although it may substantially change timings. This speculation requires systematic

investigation.

Department of Geography, Department of Geography,

University of Nottingham, University of Cambridge,

University Park, Downing Place,

Nottingham, Cambridge,

NG7 2RD, UK CB2 3EN, UK.

Acknowledgement

The work described has been undertaken as part of a five-year programme of research

entitled Disease in War, 18501990: geographical patterns, spread and demographic impact,

funded by the Leverhulme Trust. Their financial support is gratefully acknowledged.

Notes

[1] R. M. Garfield and A. I. Neugat, Epidemiologic analysis of warfare: a historical review,Journal of the American Medical Association 266 (1991) 68892; H. O. Lancaster, Expectationsof Life: A Study in Demography, Statistics, and History of World Mortality (New York 1990)31440.

[2] F. Prinzing, Epidemics Resulting from Wars (Oxford 1916); S. Dumas and K. O. Vedel-

Petersen,Losses of Life Caused by War (Oxford 1923).[3] F. Prinzing, op. cit., 171.[4] Ibid., 186.[5] K. de Bevoise,Agents of Apocalypse: Epidemic Disease in the Colonial Philippines (Princeton

1995).[6] See, for example: G. F. Pyle, Diffusion of cholera in the United States, Geographical Analysis

1 (1969) 5975; A. D. Cliff, P. Haggett, J. K. Ord and G. R. Versey, Spatial Diffusion: AnHistorical Geography of Epidemics in an Island Community (Cambridge 1981) 2732; R. F.Stock, Cholera in Africa: Diffusion of the Disease 19701975 with Particular Emphasis onWest Africa(London 1976); K. D. Patterson, Cholera diffusion in Russia, 18231923, SocialScience and Medicine 38 (1995) 117191.

[7] R. C. Ileto, Cholera and the origins of the American sanitary order in the Philippines, inD. Arnold (Ed.), Imperial Medicine and Indigenous Societies (Manchester 1988) 12548; R.Sullivan, Cholera and colonialism in the Philippines, 18991903, in R. MacLeod and M.Lewis (Eds), Disease, Medicine and Empire: Perspectives on Western Medicine and the

Experience of European Expansion (London 1988) 284300; de Bevoise,op. cit.[8] United States Public Health Service,Public Health Reports (Washington, D.C.).[9] J. C. Perry was appointed to the post of Chief Quarantine Officer in January 1900. He

retained this position until March 1903, when he was succeeded by Victor G. Heiser.[10] The role of islands as laboratories for the study of epidemiological diffusion processes is

discussed in: Cliff, Haggett, Ord and Versey, op. cit.; A. D. Cliff, P. Haggett and R. Graham,Reconstruction of diffusion processes at different geographical scales: the 1904 measlesepidemic in northwest Iceland, Journal of Historical Geography 9 (1983) 2946; A. D. Cliffand P. Haggett, The epidemiological significance of islands, Health and Place 1 (1995)199209.

[11] United States Bureau of the Census, Census of the Philippine Islands (Volumes IIV)(Washington D.C., 1905).

[12] Ibid.[13] de Bevoise,op. cit., 18.[14] See note 9.

[15] See note 7.


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[16] de Bevoise,op. cit.; Ileto, op. cit.[17] United States Public Health Service,op cit. XVII (1902) 1759.[18] Ibid., 2131.[19] de Bevoise,op. cit., 178.[20] Sullivan,op. cit.[21] Ileto, op. cit., 1289; de Bevoise, op. cit., 1789.[22] Chief Surgeons Report, Third Separate Brigade, quoted in Ileto, op. cit., 129.[23] See, for example, de Bevoise,op. cit., 1789.[24] R. S. Speck, Cholera, in K. F. Kiple (Ed.),The Cambridge World History of Human Disease

(Cambridge 1993) 6429.[25] The geographical dispersion of the various nineteenth-century global pandemics of Asiatic

cholera is mapped in A. D. Cliff and P. Haggett, Atlas of Disease Distributions: AnalyticApproaches to Epidemiological Data (Blackwell 1988) 5.

[26] de Bevoise,op. cit.

[27] United States Public Health Service, op. cit. The nature and scope of the informationincluded in the Public Health Reports is reviewed in: A. D. Cliff, P. Haggett, M. Smallman-Raynor, et al., The importance of long-term records in public health surveillance: the USweekly sanitation reports, 18881912, revisited,Journal of Public Health Medicine 19 (1987)7684; A. D. Cliff, P. Haggett and M. Smallman-Raynor, Deciphering Global Epidemics.Analytical Approaches to the Disease Records of World Cities, 18881912 (Cambridge 1998).

[28] See, for example, Annual Report of the Philippines Commission, 1903 (Part II, AppendixB) (Washington D.C. 1904).

[29] United States Bureau of the Census,op. cit.[30] Ibid.[31] Ibid.[32] The national series in Figure 2 have been formed by summing the weekly counts of cholera

cases, and cholera deaths, recorded in the Public Health Reports for each of 570 infectedmunicipalities, March 1902February 1904.

[33] Waves I and II were formally defined by reducing the national series of cholera cases in

Figure 2 to standard normal score form. A sustained weekly score of less than 05 standarddeviations below the zero mean was identified between week 51 (7 March 1903) and week60 (9 May 1903). In this manner, wave I was defined as weeks 150 (22 March 190228February 1903) and wave II as weeks 61103 (16 May 19036 February 1904).

[34] M. Smallman-Raynor and A. D. Cliff, The Philippines Insurrection and the 19024 choleraepidemic II: diffusion patterns in war and peace, Journal of Historical Geography 24, 2(1997) (in press).

[35] Only those areas classified as municipalities under the 1903 census were included in thepresent analysis.

[36] Marinduque, a sub-province of Tayabas, was classified as a separate province for thepurposes of the present analysis.

[37] United States Public Health Service,op. cit., XVII (1902) 716.[38] Ibid., 1090.[39] Speculation concerning the importation of cholera with fresh vegetables rested with the

traditional use of human manure by Chinese farmers; see Sullivan, op. cit. In his dispatchof 30 March 1902, the Chief Quarantine Officer explained that Manila was the greatestvegetable market in the Orient, as nothing of that character is produced here, all suchsupplies have to be imported, and all green vegetables such as cabbage, celery, lettuce, andcauliflower have come from the Canton districts [United States Public Health Service, op.cit., XVII (1902) 108990]. In a later communication, the Quarantine Officer dismissedspeculation concerning another possible source of the disease (Hong Kong) on the groundsof available epidemiological evidence (Ibid., 1531).

[40] United States Public Health Service,op. cit., XVII (1902) 1090.[41] Ibid., 132930.[42] Ibid., 1759.[43] Ibid., 21302.[44] Ibid.[45] Ibid. See also Ileto, op. cit.[46] United States Public Health Service,op. cit., XVII (1902) 132931.

[47] Ibid., 20745.


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[48] Ibid., 2483.[49] Ibid., 2771.[50] Ibid., 22401.[51] Ibid., 2488; United States Public Health Service, op. cit., XVIII (1903) 1089.[52] Ibid., 46.[53] United States Bureau of the Census,op. cit., Volume III, 47.[54] Cliffand Haggett, op. cit.[55] Ibid.[56] See Pyle,loc. cit.for a graphical approach to the problem. Pyles analysis is reworked within

a multiple regression framework in Cliff, Haggett, Ord and Versey, op. cit., 2732.[57] P. Haggett, A. D. Cliff and A. Frey, Locational Analysis in Human Geography (London

1977) 132.[58] See, for example Pyle, loc. cit.[59] Haggett, Cliffand Frey, op. cit., 11026.

[60] Ibid.[61] Ibid.[62] Cliff, Haggett, Ord and Versey, op. cit., 99102. A. D. Cliff, P. Haggett and J. K. Ord, Spatial

Aspects of Influenza Epidemics (London 1986) 1825.[63] For a formal definition of the minimum spanning tree, see Haggett, Cliffand Frey, op. cit.,

82.[64] TheBWjoin-count statistic is described in A. D. Cliffand J. K. Ord,Spatial Autocorrelation

(London 1973) 47.[65] The expectation and variance ofBWunder H0 is described in Cliffand Ord, Ibid.[66] Ibid., 48. In all instances, evaluation was for positive spatial autocorrelation under nonfree

sampling.[67] See note 7 for examples of this work.[68] Cliff, Haggett and Frey, op. cit., 132.[69] Pyle, op. cit.[70] Cliff, Haggett and Smallman-Raynor (1997), op. cit., Chapter 6.

[71] A. D. Cliff, P. Haggett and J. K. Ord, op. cit., 1825.[72] P. Haggett, Hybridizing alternative models of an epidemic diffusion process, Economic

Geography 52 (1976) 13646.

epidiomiological diffusion processes in war

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