Fermat's Library | Nonpharmaceutical Interventions Implemented by US Cities During the 1918-1919 Influenza Pandemic. annotated/explained version.

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ORIGINAL CONTRIBUTION

Nonpharmaceutical Interventions

Implemented by US Cities

During the 1918-1919 Influenza Pandemic

Howard Markel, MD, PhD

Harvey B. Lipman, PhD

J. Alexander Navarro, PhD

Alexandra Sloan, AB

Joseph R. Michalsen, BS

Alexandra Minna Stern, PhD

Martin S. Cetron, MD

HE INFLUENZA PANDEMIC OF

1918-1919 was the most deadly

contagious calamity in hu-

man history. Approximately 40

million individuals died worldwide, in-

cluding 550 000 individuals in the

United States.

1-4

The historical record

demonstrates that when faced with a

devastating pandemic, many nations,

communities, and individuals adopt

what they perceive to be effective so-

cial distancing measures or nonphar-

maceutical interventions including iso-

lation of those who are ill, quarantine

of those suspected of having contact

with those who are ill, school and se-

lected business closure, and public gath-

ering cancellations.

5,6

One compelling

question emerges: can lessons from the

1918-1919 pandemic be applied to con-

temporary pandemic planning efforts

to maximize public health benefit while

minimizing the disruptive social con-

sequences of the pandemic as well as

those accompanying public health re-

sponse measures?

7-10

Most pandemic influenza policy

makers agree that even the most rigor-

ous nonpharmaceutical interventions

are unlikely either to prevent a pan-

demic or change a population’s under-

lying biological susceptibility to the

pandemic virus. However, a growing

Author Affiliations: Center for the History of Medi-

cine, University of Michigan Medical School, Ann Ar-

bor (Drs Markel, Navarro, and Stern, and Ms Sloan

and Mr Michalsen); and Division of Global Migration

and Quarantine, Centers for Disease Control and Pre-

vention, Atlanta, Georgia (Drs Lipman and Cetron).

Corresponding Author: Martin S. Cetron, MD, Divi-

sion of Global Migration and Quarantine, Centers for

Disease Control and Prevention, 1600 Clifton Rd, Mail-

stop E-03, Atlanta, GA 30333 (mcetron@cdc.gov).

Context Acriticalquestioninpandemicinfluenzaplanningistherolenonpharmaceu-

tical interventions might play in delaying the temporal effects of a pandemic, reducing

the overall and peak attack rate, and reducing the number of cumulative deaths. Such

measures could potentially provide valuable time for pandemic-strain vaccine and anti-

viral medication production and distribution. Optimally, appropriate implementation of

nonpharmaceutical interventions would decrease the burden on health care services and

critical infrastructure.

Objectives To examine the implementation of nonpharmaceutical interventions for

epidemic mitigation in 43 cities in the continental United States from September 8,

1918, through February 22, 1919, and to determine whether city-to-city variation in

mortality was associated with the timing, duration, and combination of nonpharma-

ceutical interventions; altered population susceptibility associated with prior pan-

demic waves; age and sex distribution; and population size and density.

Design and Setting Historical archival research, and statistical and epidemiological

analyses. Nonpharmaceutical interventions were grouped into 3 major categories: school

closure; cancellation of public gatherings; and isolation and quarantine.

Main Outcome Measures Weekly excess death rate (EDR); time from the activation

of nonpharmaceutical interventions to the first peak EDR; the first peak weekly EDR; and

cumulative EDR during the entire 24-week study period.

Results There were 115 340 excess pneumonia and influenza deaths (EDR, 500/

100 000 population) in the 43 cities during the 24 weeks analyzed. Every city adopted

at least 1 of the 3 major categories of nonpharmaceutical interventions. School clo-

sure and public gathering bans activated concurrently represented the most common

combination implemented in 34 cities (79%); this combination had a median dura-

tion of 4 weeks (range, 1-10 weeks) and was significantly associated with reductions

in weekly EDR. The cities that implemented nonpharmaceutical interventions earlier

had greater delays in reaching peak mortality (Spearman r=−0.74, P!.001), lower

peak mortality rates (Spearman r =0.31, P=.02), and lower total mortality (Spearman

r=0.37, P=.008). There was a statistically significant association between increased

duration of nonpharmaceutical interventions and a reduced total mortality burden (Spear-

man r=−0.39, P=.005).

Conclusions These findings demonstrate a strong association between early, sus-

tained, and layered application of nonpharmaceutical interventions and mitigating the

consequences of the 1918-1919 influenza pandemic in the United States. In planning

for future severe influenza pandemics, nonpharmaceutical interventions should be con-

sidered for inclusion as companion measures to developing effective vaccines and medi-

cations for prophylaxis and treatment.

JAMA. 2007;298(6):644-654 www.jama.com

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body of theoretical modeling research

suggests that nonpharmaceutical inter-

ventions might play a salubrious role

in delaying the temporal effect of a pan-

demic; reducing the overall and peak

attack rate; and reducing the number

of cumulative deaths.

11-15

Such mea-

sures could potentially provide valu-

able time for production and distribu-

tion of pandemic-strain vaccine and

antiviral medication. Optimally, appro-

priate implementation of nonpharma-

ceutical interventions would decrease

the burden on health care services and

critical infrastructure.

The historical record of the 1918-

1919 influenza pandemic in the United

States constitutes one of the largest re-

corded experiences with the use of non-

pharmaceutical interventions to miti-

gate an easily spread, high mortality and

morbidity influenza virus strain (ie, a cat-

egory 4-5 pandemic using the Centers for

Disease Control and Prevention Febru-

ary 2007 Interim Pre-Pandemic Planning

Guidance).

Our study focused on this

data set by assessing the nonpharmaceu-

tical interventions implemented in 43 cit-

ies in the continental United States from

September 8, 1918, through February 22,

1919, a period that encompasses all of

the second pandemic wave (September-

December 1918) and the first 2 months

of the third wave (January-April 1919)

and represents the principal time span

of activation and deactivation of non-

pharmaceutical interventions. The pur-

pose was to determine whether city-to-

city variation in mortality was associated

with the timing, duration, and combi-

nation (or layering) of nonpharmaceu-

tical interventions; altered population

susceptibility associated with prior pan-

demic waves; age and sex distribution;

and population size and density.

METHODS

Data Collection

We combined systematic historical data

collection and contemporary epidemio-

logical and statistical analytic tools. Mor-

tality data wereobtained fromthe USCen-

sus Bureau’s Weekly Health Index

for

1918-1919, a series of reports listingtotal

deaths and death rates for 43 large US cit-

ies. These 43 cities were among the 66

most populous urban centers according

to the 1920 census, and all had a popu-

lation greater than 100 000. Of the 66

most populous cities, the remaining 23

hadincomplete archivaland mortality rec-

ords. No city with a comprehensive ar-

chival record of nonpharmaceutical in-

terventions was excluded. The Weekly

Health Index is the most complete extant

compilation of weekly pneumonia and

influenza mortality data inUS urbanareas

during the 1918-1919 pandemic.

In addition, we captured all of the

available public health documents on

nonpharmaceutical interventions imple-

mented by these 43 citiesduring the1918-

1919 pandemic, including municipal

public health department annual and

monthly reports and weekly bulletins;

every state and federalreport onthe 1918-

1919 influenza pandemic published be-

tween 1917 and 1922; US Census pneu-

monia and influenza mortality data from

1910-1920; the corpus of published his-

torical, medical, and public health litera-

ture on the 1918-1919 pandemic; 86 dif-

ferent newspapers from the 43 different

cities; records of US military installations

between 1917-1920; and additionalhold-

ings housedin several major libraries and

archival repositories (the complete bib-

liography of the 1144 primary and sec-

ondary sources is available as an online

supplement at http://www.cdc.gov

/ncidod/dq/index.htm).

17-23

Data Analysis

From the census reports, we extracted

the weekly pneumonia and influenza

mortality data covering the 24 weeks

from September 8, 1918, through Feb-

ruary 22, 1919, for the 43 US cities. In

1920, these 43 cities had a combined

population of approximately 23 mil-

lion (22% of the total US population). A

small number of missing values (846

[0.6%] of 136 563 deaths) was im-

puted. Using estimated weekly baseline

pneumonia and influenza death rates

generated from the 1910-1916 median

monthly values found by Collins et al,

weekly excess death rates (EDR) were

computed. Based on available mortality

data and epidemiological reports from

that era, as well as a recent retrospec-

tive statistical analysis, we estimated that

those who succumbed to influenza con-

tracted it 10 days earlier.

3,24-27

The onset of the epidemic in a par-

ticular city was estimated as either the

day of the first reported pneumonia and

influenza case, or the calendar day of

the first recorded pneumonia and in-

fluenza death minus 10 days, which-

ever was earlier. Information on non-

pharmaceutical interventions was

captured by reviewing at least 2 daily,

high-circulation newspapers for each

city and available municipal or state

health reports. Nonpharmaceutical in-

terventions were grouped into 3 ma-

jor categories: school closure; public

gathering bans; and isolation and quar-

antine. We also considered an addi-

tional general category of ancillary non-

pharmaceutical interventions (eg,

altering work schedules, limited clo-

sure or regulations of businesses, trans-

portation restrictions, public risk com-

munications, face mask ordinances).

Nonpharmaceutical interventions

were considered either activated (“on”)

or deactivated (“off”), according to data

culled from the historical record and

daily newspaper accounts. Specifi-

cally, these nonpharmaceutical inter-

ventions were legally enforced and af-

fected large segments of the city’s

population. Isolation of ill persons and

quarantine of those suspected of hav-

ing contact with ill persons refers only

to mandatory orders as opposed to vol-

untary quarantines being discussed in

our present era. School closure was con-

sidered activated when the city offi-

cials closed public schools (grade school

through high school); in most, but not

all cases, private and parochial schools

followed suit. Public gathering bans

typically meant the closure of saloons,

public entertainment venues, sport-

ing events, and indoor gatherings were

banned or moved outdoors; outdoor

gatherings were not always canceled

during this period (eg, Liberty bond pa-

rades); there were no recorded bans on

shopping in grocery and drug stores.

Based on an estimated 10-day time

frame between disease onset and death,

INTERVENTIONS DURING 1918-1919 INFLUENZA PANDEMIC

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we estimated that the association of

nonpharmaceutical interventions with

reductions in EDR occurred 10 days

after their actual date of implemen-

tation.

3,24-27

To test the association of the layering

and timing of nonpharmaceutical inter-

ventions with mortality, an analysis of

variance (ANOVA) model was con-

structed with weekly EDR as the depen-

dent variable and epidemiological week,

city, andthe status (on/off ) of everycom-

bination ofnonpharmaceutical interven-

tions as the independent variables. Inthe

ANOVA model, each possible combina-

tion ofnonpharmaceutical interventions

was treated as an independent variable

to testfor layering effects. Any factorwith

a P value of less than .10 was included

in the model. Because there is ambigu-

ity overthe rigor withwhich the category

of ancillary nonpharmaceutical interven-

tions was applied, enforced, and deac-

tivated, we focused primarily on the 3

major categories of nonpharmaceutical

interventions discussed above and we

included the ancillary nonpharmaceu-

tical interventions in the multivariate

model for purposes of completeness.

We defined additional outcome (de-

pendent) variables: (1) the time to first

peak as the time in days from the acti-

vation of the first major category of non-

pharmaceutical interventions to the date

of the first peak EDR; (2) the magni-

tude of the first peak as the first peak

weekly EDR; and (3) the mortality bur-

den as the cumulative EDR during the

entire 24-week study period.

We also defined the following inde-

pendent variables. The first was the

public health response time (PHRT) as

the time in days (either positive or nega-

tive) between the date when weekly

EDR first exceeds twice the baseline

pneumonia and influenza death rate

(2"baseline; ie, when the mortality rate

begins to accelerate) and the activa-

tion of the first major nonpharmaceu-

tical interventions. Interventions that

occurred prior to this reference point

are recorded as negative PHRT values,

indicating that public health officials re-

sponded to events prior to the accel-

eration of weekly death rates. How-

ever, most cities had positive PHRT in

that they reacted after the 2" baseline

mortality threshold, indicating that the

epidemic had already entered its accel-

eration phase. The second indepen-

dent variable was total days of non-

pharmaceutical interventions, which

was defined as the total cumulative

number of days that nonpharmaceuti-

cal interventions from the 3 major cat-

egories were activated during the en-

tire 24-week study period.

The ANOVA models were based on

the study design of a 43 (city)" 24

(week) factorial design without replica-

tion. Because there is no replication, the

city" week interaction term was treated

as the error term in the multivariate analy-

sis. We considered 4 different nonphar-

maceutical interventions. Hence, there

are 15 different combinations of these

interventions (excluding the no inter-

vention combination). Each of these 15

combinations was either implemented

(on) or not implemented (off) in each

city for each week. Thus, the effects of

each of these combinations of nonphar-

maceutical interventions are included in

the city" week interaction term. Each of

these terms (along with their " city and

"week interaction terms) were extracted

from the original city" week interac-

tion term. The remaining unexplained

variation was used as the error term in

the ANOVA model. The remaining error

term is likely to be larger than a true error

term generated through replication so the

analysis of any effects using this error

term can be expected to be conserva-

tive. Such a factorial model without rep-

lication can be used to test hypotheses

but the lack of natural error in the model

makes estimates or predictions from the

model such as effect size measures and

confidence intervals nonestimable.

We also generated scatterplots and

Spearman rank correlation coefficients

to explore the associations between

PHRT and each of the 2 additional de-

pendent variables and associations be-

tween total days of nonpharmaceutical

interventions and mortality burden. We

further investigated these associations by

using box plots and Wilcoxon rank sum

tests to compare the outcomes for the cit-

ies above and below the median of each

independent variable.

We also generated scatterplots and

Spearman rank correlation coefficients

to explore other potential or confound-

ing associations (as independent deter-

minants): (1) EDR in the 4 successive

waves of the pandemic; (2) city-specific

population size vs EDR; (3) city-

specific population density vs EDR; (4)

city-specific population age distribu-

tion vs EDR; and (5) city-specific sex dis-

tribution vs EDR. Analyses were per-

formed using SAS statistical software

version 9.1 (SAS Institute Inc, Cary, NC).

RESULTS

There were 115 340 excess pneumonia

and influenza deaths (EDR, 500/

100 000 population) in the 43 cities dur-

ing the 24 weeks analyzed. T

ABLE 1

shows considerable city-to-city varia-

tion in mortality profiles and interven-

tion characteristics; lists the earliest re-

ported dates of the first pneumonia and

influenza cases by city, mortality accel-

eration (2" baseline EDR), first imple-

mentation of nonpharmaceutical inter-

ventions, and first peak EDR; and lists

the values for each of the independent

and outcome variables described above.

ABLE 2 shows the categories of non-

pharmaceutical intervention combina-

tions, the number of cities implement-

ing those combinations, and the median

and range of duration of implementa-

tion by each of the 43 cities during the

study period. Every city adopted at least

1ofthe3majorcategoriesofnonphar-

maceutical interventions; 15 applied all

3 categories of nonpharmaceutical in-

terventions concurrently. School clo-

sure concurrently combined with pub-

lic gathering bans represented the most

common combination, implemented in

34 cities (79%) for a median duration

of 4 weeks (range, 1-10 weeks). School

closure was ultimately used in some

combination with the other categories

of nonpharmaceutical interventions by

40 cities (93%). Three cities never of-

ficially closed their schools (New York

City, New York, New Haven, Connecti-

cut, and Chicago, Illinois, although the

latter reported a student absenteeism

INTERVENTIONS DURING 1918-1919 INFLUENZA PANDEMIC

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rate of #45% at the peak of its epi-

demic); 25 cities closed their schools

once, 14 closed them twice, and 1 (Kan-

sas City, Missouri) closed its schools 3

times. Schools were officially closed a

median of 6 weeks (range, 0-15 weeks).

The ANOVA multivariate model had

an r

of 86.7% (P! .001). Nonpharma-

ceutical interventions were a significant

Table 1. Characteristics of Influenza Pandemic for 43 US Cities Between September 8, 1918, and February 22, 1919

City

First

Case

Date

Mortality

Acceleration

Date

Date of First

Nonpharmaceutical

Intervention

Public

Health

Response

Time, d

Total No. of Days of

Nonpharmaceutical

Interventions

Date of

Peak

Excess

Death

Rate

Time to

Peak, d

Magnitude of

First Peak,

Excess

Deaths/

100 000

Population

Excess

Pneumonia

and

Influenza

Mortality,

Deaths/

100 000

Population

Albany, NY 9/27 10/6 10/9 3 47 10/24 15 161.8 553.2

Baltimore, MD 9/18 9/29 10/9 10 43 10/18 9 182.1 559.3

Birmingham, AL 9/24 9/30 10/9 9 48 10/22 13 70.9 591.8

Boston, MA 9/4 9/12 9/25 13 50 10/3 8 159.9 710.0

Buffalo, NY 9/24 9/28 10/10 12 49 10/22 12 140.9 529.5

Cambridge, MA 9/4 9/11 9/25 14 49 10/3 8 125.5 541.0

Chicago, IL 9/17 9/28 9/26 −2 68 10/21 25 84.8 373.2

Cincinnati, OH 9/24 10/4 10/6 2 123 10/24 18 67.6 451.2

Cleveland, OH 9/20 10/7 10/5 −2 99 10/31 26 83.6 474.0

Columbus, OH 9/20 10/6 10/11 5 147 10/24 13 47.3 311.7

Dayton, OH 9/20 10/5 9/30 −5 156 10/20 20 87.8 410.0

Denver, CO 9/17 9/27 10/6 9 151 10/20 14 55.0 630.9

Fall River, MA 9/9 9/16 9/26 10 60 10/12 16 165.2 621.3

Grand Rapids, MI 9/23 10/2 10/19 17 62 10/25 6 15.0 210.5

Indianapolis, IN 9/22 9/30 10/7 7 82 10/18 11 38.8 290.0

Kansas City, MO 9/20 9/26 9/26 0 170 10/27 31 58.1 579.8

Los Angeles, CA 9/27 10/6 10/11 5 154 10/30 19 64.2 493.8

Louisville, KY 9/13 10/1 10/7 6 145 10/20 13 74.8 406.4

Lowell, MA 9/9 9/16 9/27 11 59 10/10 13 123.1 522.9

Milwaukee, WI 9/14 10/6 10/11 5 132 10/23 12 36.4 291.5

Minneapolis, MN 9/21 10/6 10/12 6 116 10/24 18 37.6 267.1

Nashville, TN 9/21 10/6 10/7 1 55 10/16 9 160.1 610.4

New Haven, CT 9/14 9/23 10/15 22 39 10/24 9 109.5 586.5

New Orleans, LA 9/10 10/1 10/8 7 78 10/20 12 172.9 734.0

New York City, NY 9/5 9/29 9/18 −11 73 10/23 35 90.1 452.3

Newark, NJ 9/6 9/30 10/10 10 33 10/22 12 101.5 533.0

Oakland, CA 10/1 10/8 10/12 4 127 10/30 18 107.0 506.2

Omaha, NE 9/18 10/4 10/5 1 140 10/18 13 81.7 554.0

Philadelphia, PA 8/27 9/25 10/3 8 51 10/16 13 249.7 748.4

Pittsburgh, PA 9/4 9/27 10/4 7 53 11/5 32 130.7 806.8

Portland, OR 10/2 10/7 10/11 4 162 11/2 22 59.4 505.2

Providence, RI 9/8 9/17 10/6 19 42 10/17 11 105.2 574.2

Richmond, VA 9/21 9/29 10/6 7 60 10/16 10 112.2 508.3

Rochester, NY 9/22 10/6 10/9 3 54 10/26 17 70.2 359.1

St Louis, MO 9/23 10/7 10/8 1 143 10/29 21 30.0 358.0

St Paul, MN 9/21 10/2 11/6 35 28 11/12 6 55.6 413.2

San Francisco, CA 9/24 10/7 10/18 11 67 10/29 11 143.0 672.7

Seattle, WA 9/24 10/1 10/6 5 168 10/23 17 49.5 414.1

Spokane, WA 9/28 10/9 10/10 1 164 11/5 26 66.0 481.8

Syracuse, NY 9/12 9/18 10/7 19 39 10/14 7 145.4 541.4

Toledo, OH 9/21 10/13 10/15 2 102 10/25 10 54.8 294.5

Washington, DC 9/11 9/23 10/3 10 64 10/15 12 140.1 607.6

Worcester, MA 9/9 9/12 9/27 15 44 10/7 10 126.1 654.7

Defined as 2 " baseline death rate.

Defined as days between 2 " baseline death rate and first nonpharmaceutical intervention.

Weekly excess death rate.

Total excess death rate through 24 weeks.

INTERVENTIONS DURING 1918-1919 INFLUENZA PANDEMIC

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source of the variation in the weekly

EDRs within and between the cities. The

ANOVA results are shown in T

ABLE 3.

The multivariate model demonstrates

that layered nonpharmaceutical inter-

ventions generally had a more signifi-

cant association with weekly EDR than

individual nonpharmaceutical interven-

tions. Specifically, combinations of non-

pharmaceutical interventions includ-

ing school closure and public gathering

bans appeared to have the most signifi-

cant association with weekly EDR (ie, the

lowest P values, most were P!.001). The

large number of significant nonpharma-

ceutical interventions" week interac-

tions in the model confirms that the tim-

ing of the implementation of a given

combination of nonpharmaceutical inter-

ventions was a significant factor in reduc-

ing mortality. One caveat is persistent

nonpharmaceutical interventions" city

interactions, meaning that the success of

astrategyofnonpharmaceuticalinter-

ventions in a particular city does not uni-

formly translate to all other cities. The 2

outlier cities in our study, Grand Rap-

ids, Michigan, and St Paul, Minnesota,

exemplify this point.

The scatterplots in F

IGURE 1A,

Figure 1B, and Figure 1C display the

associations between the PHRT and

each of the 3 dependent variables.

Figure 1A displays the association be-

tween PHRT in days and time to first

peak EDR; cities that implemented non-

pharmaceutical interventions earlier

had greater delays in reaching peak

mortality (Spearman r =−0.74,

P! .001). Figure 1B shows the asso-

ciation between PHRT and the magni-

tude of the first peak EDR; cities that

implemented nonpharmaceutical in-

terventions earlier had lower peak mor-

tality rates (Spearman r=0.31, P=.02).

Figure 1C depicts the association be-

tween PHRT and total mortality bur-

den; cities that implemented nonphar-

maceutical interventions earlier

experienced a lower total mortality

(Spearman r=0.37, P =.008). In sum-

mary, when comparing the 21 cities

with earlier (less than the median)

PHRT with the 21 cities with the later

(greater than the median) PHRT, there

are statistically significant differences

for each of the outcome measures

(P$ .001; T

ABLE 4).

Figures 1C and 1D show the associa-

tion betweenearly, sustained, and layered

application of nonpharmaceutical inter-

ventions and total excess pneumonia and

influenza mortality burden in 43 cities.

Figure 1C shows the statistically signifi-

cant association between PHRT and total

mortality burden. Figure 1D shows a sta-

tistically significant association between

increased duration of nonpharmaceuti-

cal interventions and a reduced total

mortality burden (Spearman r=−0.39,

P=.005).Insummary,the 21 citiesthat

hadearlier PHRT(ie, less thanthe median)

and the most sustained and most days of

nonpharmaceutical interventions had a

statistically significant reduction inexcess

pneumonia and influenza mortality rates

compared with the 21 cities that had later

PHRT and fewer days of nonpharmaceu-

tical interventions (Table 4).

IGURE 2 shows the aggregate city

mortality curves by region (East, Mid-

west and South, and West). F

IGURE 3

displays 4 city-specific mortality curves,

including weekly EDR and the non-

pharmaceutical interventions imple-

mented as well as their activation and

deactivation dates for St Louis, Mis-

souri, New York City, Denver, Colo-

rado, and Pittsburgh, Pennsylvania.

These 4 cities were chosen because they

indicate the broad spectrum of out-

comes seen in the 43 cities studied as

well as for their geographical and so-

cial diversity. (The mortality curves for

all 43 cities are available at http://www

.cdc.gov/ncidod/dq/index.htm.) Over-

all, cities that implemented nonphar-

maceutical interventions earlier

experienced associated delays in the

time to peak mortality, reductions in the

magnitude of the peak mortality, and

decreases in the total mortality burden.

In exploring alternative and poten-

tially confounding explanations for varia-

tion in city-specific EDR, we used a scat-

terplot to compare the cumulative EDR

of the 43 cities during pandemic waves

1(February-May1918),2(September-

December 1918), 3 ( January-April 1919),

and 4 (January-April 1920).

2,3

We found

no statistically significant association of

the EDR across the 43 cities when com-

paring successive waves. Specifically, the

severity or occurrence of wave 1 is not

associated, either positively or nega-

tively, with the severity of wave 2; the

severity of wave 2 is not associated with

the severity of wave 3; and the severity

of wave 3 is not associated with the sever-

ity of wave 4 (figures appear in the online

supplement at http://www.cdc.gov

/ncidod/dq/index.htm).

28,29

Publishedvirological evidencefor strain

variation during wave 2 is limited to a

single genotypic variant withoutevidence

for significant phenotypic change in

virulence.

30-33

While plausible, novirologi-

Table 2. Nonpharmaceutical Interventions Implemented in 43 US Cities Between September

8, 1918, and February 22, 1919

Type of Nonpharmaceutical Intervention

No. (%) of Cities

Implementing

Nonpharmaceutical

Intervention

for #1 wk (N = 43)

Median (Range)

Duration of

Nonpharmaceutical

Intervention, wk

Isolation or quarantine only 15 (35) 1 (1-10)

School closure only 22 (51) 1 (1-7)

Public gathering ban only 6 (14) 1.5 (1-5)

Isolation and quarantine and school closure 2 (5) 5.5 (4-7)

Isolation and quarantine and public gathering ban 4 (9) 4 (2-5)

School closure and public gathering ban 34 (79) 4 (1-10)

Isolation and quarantine, school closure,

and public gathering ban

15 (35) 4 (2-6)

Cities often implemented more than 1 nonpharmaceutical intervention combination during the outbreak period, so

the total adds to more than 100%. The number of categories of nonpharmaceutical interventions implemented dur-

ing some part of the outbreak was 1 in 1 city, 2 in 23 cities, and 3 in 19 cities. The total number of weeks that at least

1 nonpharmaceutical intervention was implemented was 4 in 6 cities, 5 in 6 cities, 6 in 8 cities, 7 in 3 cities, 8 in 6

cities, 10 in 5 cities, 11 in 4 cities, 13 in 1 city, 14 in 2 cities, 15 in 1 city, and 16 in 1 city. No cities had at least 1

nonpharmaceutical intervention implemented for durations of 9 and 12 weeks.

INTERVENTIONS DURING 1918-1919 INFLUENZA PANDEMIC

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cal evidence yet exists to explain the per-

plexing mortality difference between the

spring 1918 wave, which was reportedly

milder, and the subsequent fall and win-

ter waves. Additional studies may clarify

the understanding of the 1918 pandem-

ic’s wave phenomena.

Similarly, scatterplots comparing the

cumulative EDR to thecity-specific popu-

lation size and density; sex distribution;

and proportion of ages of younger than

1monthto5years,15to40years,and

older than 65 years, which corresponded

to high reported specific mortality rates

in 1918 demonstrated no association.

Among the 43 cities we investigated, nei-

ther the city’s populationsize, density, sex

distribution, nor age distribution ac-

counted for the differences in mortality

(figures appear in supplement at http:

//www.cdc.gov/ncidod/dq/index.htm).

Table 3. Multivariate Model Showing Effect of Combinations of Nonpharmaceutical Interventions on Weekly Excess Death Rates for 43 US

Cities Between September 8, 1918, and February 22, 1919

Source of Variation df

Sum of

Squares

Mean

Square F Score P Value

Type of confounders

Week 29 75 677.0 2609.6 16.24 !.001

City 42 65 557.9 1560.9 9.72 !.001

1 Nonpharmaceutical intervention

School closure 1 1288.7 1288.7 8.02 .005

" Week 8 4551.8 569.0 3.54 !.001

Banning public gatherings 1 1342.0 1342.0 8.35 .004

Isolation and quarantine 1 911.1 911.1 5.67 .02

" City 10 3976.5 397.7 2.48 .006

Ancillary nonpharmaceutical interventions 1 897.3 897.3 5.59 .02

" Week 13 6122.4 471.0 2.93 !.001

" City 12 10 257.6 854.8 5.32 !.001

2 Nonpharmaceutical interventions

School closure and banning public gatherings 1 681.3 681.3 4.24 .04

" Week 9 6497.0 721.9 4.49 !.001

" City 13 6229.9 479.2 2.98 !.001

School closure and isolation and quarantine 1 2335.3 2335.3 14.54 !.001

" Week 4 2434.2 608.6 3.79 .005

Banning public gatherings and isolation and quarantine 1 292.3 292.3 1.82 .18

" Week 1 563.9 563.9 3.51 .06

Banning public gatherings and ancillary nonpharmaceutical interventions 1 272.6 272.6 1.70 .19

" Week 4 7444.6 1861.1 11.59 !.001

" City 4 5547.6 1386.9 8.63 !.001

Isolation and quarantine and ancillary nonpharmaceutical interventions 1 48.1 48.1 0.30 .58

" Week 2 1507.6 753.8 4.69 .009

" City 2 824.7 412.4 2.57 .08

3 Nonpharmaceutical interventions

School closure, banning public gatherings, and isolation and quarantine 1 762.4 762.4 4.75 .03

" Week 2 2239.3 1119.7 6.97 .001

School closure, banning public gatherings, and ancillary

nonpharmaceutical interventions

1 691.6 691.6 4.41 .04

" Week 10 12 260.5 1226.0 7.63 !.001

" City 26 51 423.8 1977.8 12.31 !.001

School closure, isolation and quarantine, and ancillary

nonpharmaceutical interventions

1 3451.1 3451.1 21.48 !.001

" Week 4 2493.5 623.4 3.88 .004

Banning public gatherings, isolation and quarantine, and ancillary

nonpharmaceutical interventions

1 51.9 51.9 0.32 .57

" Week 8 4535.2 566.9 3.53 !.001

4 Nonpharmaceutical interventions

School closure, banning public gatherings, isolation and quarantine,

and ancillary nonpharmaceutical interventions

1 503.7 503.7 3.14 .08

" Week 9 6068.3 674.3 4.20 !.001

" City 13 23 509.7 1808.4 11.26 !.001

Error 770 123 691.2 160.6

= 86.7%

INTERVENTIONS DURING 1918-1919 INFLUENZA PANDEMIC

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COMMENT

During the 1918-1919 influenza pan-

demic, all 43 cities eventually imple-

mented nonpharmaceutical interventions

but the time of activation, duration, and

choice or combination of these nonphar-

maceutical interventions appear to have

been keyfactors in their success orfailure.

In 1918, decisions to activate nonphar-

maceutical interventions were typically

triggered by excess morbidity, mortality,

or both, as well as situational awareness

ofother communitiesnearand far.Because

discerning precisely the first arrival of

pandemic virus in a community was dif-

ficult, we chose to measure public health

response time in reference to excess

pneumonia and influenza mortality (ie,

when weekly EDR first crossed the thresh-

old of 2" the baseline and the mortality

rates entered an acceleration phase).

Figure 1. Scatterplot of Public Health Response Time for 43 US Cities From September 8, 1918, Through February 22, 1919

New York City, NY

–15 –10 –5 0 5 10 15 20 25 30 35

Public Health Response Time, d

Time to First Peak

Excess Death Rate, d

Time to first mortality peak by public

health response time

Pittsburgh, PA

St Louis, MO

Denver, CO

St Paul, MN

Grand Rapids, MI

250

200

150

New York City, NY

–15 –10 –5 0 5 10 15 20 25 30 35

Public Health Response Time, d

Excess Deaths/100

000 Population

Magnitude of first mortality peak by public

health response time

Pittsburgh, PA

St Louis, MO

Denver, CO

St Paul, MN

Grand Rapids, MI

New York

City, NY

500

600

700

800

400

300

200

500

600

700

800

400

300

200

–15 –10 –5 0 5 10 15 20 25 30 35

Public Health Response Time, d

Excess Deaths/100

000 Population

Total excess pneumonia and influenza mortality

by public health response time

Pittsburgh, PA

St Louis, MO

–0.74

P<.001

0.31

.02

Denver, CO

St Paul, MN

Grand Rapids, MI

New York City, NY

20 40 16060 80 100 120 140

Total No. of Days of Nonpharmaceutical Interventions

Excess Deaths/100

000 Population

Total excess pneumonia and influenza mortality by

total No. of days of nonpharmaceutical interventions

Pittsburgh, PA

St Louis, MO

Denver, CO

St Paul, MN

Grand Rapids, MI

0.37

.008

–0.39

.005

The 4 cities represented by black circles are discussed further in the text. The 2 citie s represented by blue circles are outliers chosen to demonstrate that the associations

shown are not perfect. The Spearman rank correlation coefficient was used.

Table 4. Implementation Strategy of Nonpharmaceutical Interventions for 21 Cities Between September 8, 1918, and February 22, 1919

Outcome Variable

Public Health Response Time, d

Value

Early (!7 d)

Late (#7 d)

25th

Percentile

50th

Percentile

75th

Percentile

25th

Percentile

50th

Percentile

75th

Percentile

Time to peak, d 13 18 22 9 11 13 !.001

Magnitude of first peak (weekly EDR) 54.7 67.6 84.8 101.5 125.8 145.4 .001

Excess pneumonia and influenza

mortality rate (total EDR)

359.1 451.2 505.2 529.5 580.3 654.7 !.001

Total Days of Nonpharmaceutical Interventions

Most (#65 d) Least (!65 d)

Excess pneumonia and influenza

mortality rate (total EDR)

358.0 451.2 505.2 529.5 559.3 610.4 !.001

Abbreviation: EDR, excess death rate.

INTERVENTIONS DURING 1918-1919 INFLUENZA PANDEMIC

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Hence, the difference in time between the

first nonpharmaceutical interventionsand

this excess mortality threshold may be a

positive or negative value. For example,

in Philadelphia,Pennsylvania, which was

affected early and was unprepared to re-

spond, the PHRT was 8 and the EDR was

approximately 37/100 000 population at

the point of implementing nonpharma-

ceutical interventions; in contrast, New

York City’s PHRT was −11 days and the

EDR was 0/100 000 population at the

point of implementing nonpharmaceu-

tical interventions. New York City re-

sponded toits first influenza cases and the

perceived severity of the epidemic in

nearby cities without waiting for excess

deaths to accumulate.

The US Centersfor DiseaseControl and

Prevention’s newlyreleased interim com-

munity mitigation guidance recommends

activating nonpharmaceutical interven-

tions when outbreaks due to a pandemic

virus strain first are confirmed in a state

or metropolitan service region.

Several

theoretical models suggest that the effect

of targeted, layered strategies for nonphar-

maceutical interventions may be opti-

mized when community influenza attack

rates are 1% or lower.

11-15

Given the ex-

ponential growth of an unmitigated in-

fluenza pandemic, it is reasonable to ex-

pect that the timing of interventions will

be among the most critical factors. Such

expectations and biological realities are

consistent with our observations of the

1918 pandemic, when rapidpublic health

response time was a critical factor in the

successful applicationof nonpharmaceu-

tical interventions.

Late interventions, regardless of their

duration or permutation of use, al-

most always were associated with worse

outcomes. However, timing alone was

not consistently associated with suc-

cess. The combination and choice of

nonpharmaceutical interventions also

appeared to be critical as confirmed by

the multivariate model.

For example, New York City reacted

earliest to the gathering influenza crisis,

primarily with the sustained (%10weeks

beginning September 19, 1918) and rig-

idly enforced application of compulsory

isolationand quarantineprocedures,along

with anenforced staggered business hour

ordinance from October 5 through No-

vember 3, 1918.

During this era, New

York City’s health department was re-

nowned internationally for its innovative

policies of mandatory case reporting and

rigidly enforced isolation and quarantine

procedures.

Typically, individualsdiag-

nosed with influenza wereisolated in hos-

pitals or makeshift facilities, while those

suspected to have contact with an ill per-

son (but who were not yet ill themselves)

were quarantined in their homes with an

official placard declaring that location to

be under quarantine. New York City

mounted an early and sustained response

to the epidemic and experienced thelow-

est death rate on the Eastern seaboard but

it did not layer its response. New York

City’s cumulative mortality burden, 452/

100 000, ranked 15 out of the 43 cities

studied.

In contrast, Pittsburgh, under orders

from the Pennsylvania health depart-

ment, executed a public gathering ban

on October 4, 1918, but city officials de-

layed until October 24 before imple-

menting school closure. A week later, on

November 2, the state rescinded public

gathering bans. The city applied its non-

pharmaceutical interventions late and in-

dividually rather than combined. Pitts-

burgh’s cumulative excess mortality

burden (EDR=807/100 000) ranked 43

out of 43 cities during the study period.

However, the benefits of theseinterven-

tions were not equally distributed. Those

cities acting in a timely and comprehen-

sive manner appearto havebenefited most

in terms of reductions in total EDR. For

example, St Louis, which implemented

arelativelyearly,layeredstrategy(school

closure and cancellation of public gath-

erings), and sustained these nonpharma-

ceutical interventions for about 10 weeks

each, did not experience nearly as delete-

rious an outbreak as 36 other communi-

ties in the study (cumulative EDR=358/

100 000 population).

The 1918 experience suggests that sus-

tained nonpharmaceutical interven-

tions are beneficial and need to be “on”

throughout the particular peak of a lo-

cal experience. Many of the 43 cities in

the study, particularly in the Midwest and

South and West, experienced 2 peaks of

excess pneumonia and influenza mor-

tality (eg, Birmingham, Alabama, Cin-

cinnati, Ohio, Columbus, Ohio, Den-

ver, Indianapolis, Indiana, Kansas City,

Figure 2. Aggregate Weekly Excess Death Rates for 43 US Cities by Region From September

8, 1918, Through February 22, 1919

120

100

Weekly Excess Death Rate, No. of

Deaths per 100

000 Population

Sep

1918

15 22 29 Oct

13 20 27 Nov

10 17 24 8Dec

15 22 29 Jan

1919

12 2619 9 16 23Feb

West EastMidwest and South

The total excess death rate is 555 for the East region; 413 for the Midwe st and South region; and 529 for the

West region.

INTERVENTIONS DURING 1918-1919 INFLUENZA PANDEMIC

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Louisville, Kentucky, Milwaukee, Wis-

consin, Minneapolis, Minnesota, Oak-

land, California, Omaha, Nebraska, Port-

land, Oregon, Rochester, New York, St

Louis, San Francisco, California, Se-

attle, Washington, Spokane, Washing-

ton, Toledo, Ohio; see figures in online

supplement at http://www.cdc.gov

/ncidod/dq/index.htm). These second

Figure 3. Weekly Excess Death Rates From September 8, 1918, Through February 22, 1919

Total excess death rate: 631/100

000 population

Public health response time: +9 d

Total No. of days of nonpharmaceutical

interventions: 151

100

120

110

130

140

Weekly Excess Death Rate, No. of

Deaths per 100

000 Population

Weekly Excess Death Rate, No. of

Deaths per 100

000 Population

Denver, CO

Total excess death rate: 807/100

000 population

Public health response time: +7 d

Total No. of days of nonpharmaceutical

interventions: 53

Pittsburgh, PA

Total excess death rate: 358/100

000 population

Public health response time: +1 d

Total No. of days of nonpharmaceutical

interventions: 143

100

120

110

130

140

St Louis, MO

Total excess death rate: 452/100

000 population

Public health response time: –11 d

Total No. of days of nonpharmaceutical

interventions: 73

New York City, NY

School closure

Public gathering ban

Isolation, quarantine

School closure

Public gathering ban

Other

Isolation, quarantine

Other

Weekly excess death rate

2 × baseline mortality

First pneumonia and influenza case

Oct

Sep

1918

Nov

Dec

Jan

1919

Feb

Oct

Sep

1918

Nov

Dec

Jan

1919

Feb

Oct

Sep

1918

Nov

Dec

Jan

1919

Feb

Oct

Sep

1918

Nov

Dec

Jan

1919

Feb

School closure

Public gathering ban

Other

Type and duration of nonpharmaceutical interventions are indicated under each plot. For the specific nonpharmaceutical interventions, black bars indicate activation.

Business hours restricted, streetcars’ capacity limited.

Staggered business hours, signs with “cover coughs.”

Staggered business hours, warning signs posted in theaters.

Schoolchildren given information to take home, warned not to gather in groups.

INTERVENTIONS DURING 1918-1919 INFLUENZA PANDEMIC

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peaks frequently followed the sequen-

tial activation, deactivation, and reacti-

vation of nonpharmaceutical interven-

tions, highlighting the transient

protective nature of nonpharmaceuti-

cal interventions and the need for a sus-

tained response. For example, Denver

(cumulative EDR=631/100 000 popu-

lation) responded twice with an exten-

sive menu of nonpharmaceutical inter-

ventions that included public gathering

bans, school closure, isolation and quar-

antine, and several ancillary nonphar-

maceutical interventions and these ac-

tions are reflected temporally in its

2-peak mortality curve.

Such dual-peaked cities are of particu-

lar interest because of the specificity and

temporal associations between excess

mortality and the triggers of activation

and deactivation of nonpharmaceutical

interventions and the implications for a

causal relationship. Among the 43 cit-

ies, we found no example of a city that

had a second peak of influenza while the

first set of nonpharmaceutical interven-

tions were still in effect, suggesting that

each city with a bimodal pattern served

as its own control. In dual-peaked cit-

ies, activation of nonpharmaceutical in-

terventions was followed by a diminu-

tion of deaths and, typically, when

nonpharmaceutical interventions were

deactivated, death rates increased.

History is not a predictive science.

There exist numerous well-documented

and vast differences between US society

and public health during the 1918 pan-

demic comparedwith the present. We ac-

knowledge the inherent difficulties of in-

terpreting data recorded nearly 90 years

ago and contending with the gaps, omis-

sions, and errors that may be included in

the extant historical record. The associa-

tions observed are not perfect; for ex-

ample, 2 outlier cities (Grand Rapids and

St Paul) experiencedbetter outcomeswith

less than perfect public health responses.

Future work by our research team will

explore social, political, and ecological

determinants, which may further help to

explain some of this variation.

The United States of 1918 had many

similar features to the present era: rapid

transportation in the form of trains and

automobiles; rapid means of commu-

nication in the form of the telegraph and

telephone; large, heterogeneous popu-

lations with substantial urban concen-

trations (although a much higher per-

centage of the US population lived in

rural areas compared with the pres-

ent); a news system that was able to cir-

culate information widely during the

epidemic, including many daily news-

papers and broadsheets distributed in

communities; and a wide spectrum of

public health agencies at various lev-

els of government.

When examining the 1918 pan-

demic, however, it is important to rec-

ognize the numerous social, cultural, and

scientific differences that do exist be-

tween that period and the present. For

example, the legal understanding of pri-

vacy, civil, and constitutional rights as

they relate to public health and govern-

mentally directed measures (such as mass

vaccination programs) has changed

markedly over the past 9 decades. In ad-

dition, public support of and trust in

these measures, along with trust in the

medical profession as a whole, has shifted

over time. Finally, other features of the

modern era that need to be considered

when applying lessons from history to

the present era include the increased

speed and mode of travel, above all high-

volume commercial aviation; instanta-

neous access to information via the In-

ternet and personal computers; a baseline

understanding among the general popu-

lation that the etiologic agents of infec-

tious diseases are microbial; and ad-

vances in medical technology and

therapeutics that have expanded con-

siderably the options available for deal-

ing with a pandemic.

Historical contextual issues and sta-

tistical limitations aside, the US urban

experience with nonpharmaceutical in-

terventions during the 1918-1919 pan-

demic constitutes one of the largest data

sets of its kind ever assembled in the

modern, postgerm theory era.

Our findings conform to 8 of A. Brad-

ford Hill’s 9 tenets on causal associa-

tions in the consideration of disease and

the environment.

Specifically, dur-

ing the 1918-1919 pandemic, the rela-

tion of early, sustained, and layered

nonpharmaceutical interventions to

EDR in 43 US cities demonstrate sat-

isfaction of the criteria of strength (the

magnitude and statistical significance

of our findings, which also argue against

an association by chance alone), con-

sistency (early and combined nonphar-

maceutical interventions were consis-

tently associated with reductions in

mortality, and our analysis is consis-

tent with 2 recent smaller, prelimi-

nary historical epidemiological re-

ports, although these studies look at

only 16 US urban centers, do not in-

clude actual activation and deactiva-

tion time points, duration, or layering

of nonpharmaceutical interventions,

and rely extensively on secondary his-

torical sources.

37,38

Further, our retrospective study is

consistent with the results from recent

theoretical models of the spread of a con-

temporary pandemic, which highlight

the value of early, combined, and sus-

tained nonpharmaceutical interven-

tions to mitigate a pandemic

11-15

), speci-

ficity (best demonstrated in cities with

bimodal mortality peaks when the trig-

gers were activated, deactivated, and re-

activated), temporality (interventions al-

ways preceded the reduction of EDR),

dose response (layering and increased du-

ration of the nonpharmaceutical inter-

ventions were associated with better out-

comes), biological plausibility (these

interventions reduce person-to-person

interactions and biologically would be

expected to reduce the spread of a com-

municable agent such as influenza), co-

herence (our data align with the estab-

lished body of knowledge on the

epidemiology of influenza), and anal-

ogy (isolation and social distancing have

been demonstrated as effective means of

preventing person-to-person spread of

other respiratory tract diseases, such as

rhinovirus, severe acute respiratory syn-

drome, respiratory syncytial virus, vari-

cella, and seasonal influenza).

The ninth tenet, experiment,could

not be demonstrated directly because

of the paucity of influenza pandemics

in the past century, the trend away from

such traditional public health mea-

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sures for disease control during the past

50 years, and ethical limitations of using

population-wide nonpharmaceutical in-

terventions in the absence of a serious

threat.

These findings contrast with the con-

ventional wisdom that the 1918 pan-

demic rapidly spread through each

community killing everyone in its path.

Although these urban communities had

neither effective vaccines nor antivi-

rals, cities that were able to organize and

execute a suite of classic public health

interventions before the pandemic

swept fully through the city appeared

to have an associated mitigated epi-

demic experience. Our study suggests

that nonpharmaceutical interventions

can play a critical role in mitigating the

consequences of future severe influ-

enza pandemics (category 4 and 5) and

should be considered for inclusion in

contemporary planning efforts as com-

panion measures to developing effec-

tive vaccines and medications for pro-

phylaxis and treatment. The history of

US epidemics also cautions that the

public’s acceptance of these health mea-

sures is enhanced when guided by ethi-

cal and humane principles.

39-41

Author Contributions: Drs Markel and Cetron had full

access to all of the data in the study and take respon-

sibility for the integrity of the data and the accuracy

of the data analysis.

Study concept and design: Markel, Lipman, Navarro,

Stern, Cetron.

Acquisition of data: Markel, Navarro, Sloan, Michalsen,

Stern.

Analysis and interpretation of data: Markel, Lipman,

Navarro, Sloan, Michalsen, Stern, Cetron.

Drafting of the manuscript: Markel, Lipman, Navarro,

Sloan, Michalsen, Stern, Cetron.

Critical revision of the manuscript for important in-

tellectual content: Markel, Lipman, Navarro, Stern,

Cetron.

Statistical analysis: Markel, Lipman, Cetron.

Obtained funding: Markel, Cetron.

Administrative, technical, or material support: Markel,

Navarro, Sloan, Michalsen, Cetron.

Study supervision: Markel, Cetron.

Financial Disclosures: None reported.

Funding/Support: This study was funded by a con-

tract from the US Centers for Disease Control and Pre-

vention (Sol No. 2006-N-08562, Non-Pharmaceuti-

cal Interventions Study/contract 200-2006-16894).

Role of the Sponsor: The US Centers for Disease Con-

trol and Prevention provided funding as part of pan-

demic preparedness research. Drs Cetron and Lip-

man from the Division of Global Migration and

Quarantine at the Centers for Disease Control and Pre-

vention participated as full scientific collaborators in

the investigation.

Acknowledgment: Matthew Cartter, MD, MPH,

Cleto DiGiovanni Jr, Jeffrey Duchin, MD, Bruce Gel-

lin, MD, Richard Goodman, MD, JD, Daniel Jerni-

gan, MD, MPH, Lisa Koonin, MN, MPH, Anthony

Marfin, MD, Martin Meltzer, PhD, William Thomp-

son, PhD, David Shay, MD, and Mary Wilson, MD,

provided constructive review of this manuscript. No

one metioned in this section was compensated for

contributing.

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INTERVENTIONS DURING 1918-1919 INFLUENZA PANDEMIC

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Saturated fatty acids increase levels of low-density lipo-

protein cholesterol (LDL-C) and HDL-C,

whereas trans-

fatty acids increase LDL-C level but decrease HDL-C level.

2,3

This distinction is important, because trans-fatty acids are

more strongly associated with the risk of cardiovascular dis-

ease than saturated fatty acids due to their undesirable ef-

fects on LDL-C and HDL-C levels, endothelial cell func-

tion, adipocytes, and inflammatory response.

3,4

Dae Hyun Kim, MD, MPH

dae-hyun.kim@mail.tju.edu

Department of Medicine

Jefferson Medical College

Philadelphia, Pennsylvania

Financial Disclosures: None reported.

1. Singh IM, Shishehbor MH, Ansell BJ. High-density lipoprotein as a therapeutic

target: a systematic review. JAMA.2007;298(7):786-798.

2. Kris-Etherton PM, Yu S. Individual fatty acid effects on plasma lipids and lipo-

proteins: human studies. Am J Clin Nutr.1997;65(5)(suppl):1628S-1644S.

3. Mozaffarian D, Katan MB, Ascherio A, Stampfer MJ, Willett WC. Trans fatty

acids and cardiovascular disease. NEnglJMed.2006;354(15):1601-1613.

4. Hu FB, Stampfer MJ, Manson JE, et al. Dietary fat intake and the risk of coro-

nary heart disease in women. NEnglJMed.1997;337(21):1491-1499.

In Reply: Dr Kim distinguishes the effects of saturated fatty

acids and trans-fatty acids on lipoproteins. However, re-

ports of the effect of trans-fatty acids on HDL-C have been

variable, with a large meta-analysis finding a statistically non-

significant effect on HDL-C.

In addition to increasing lev-

els of LDL-C, trans-fatty acids promote vascular inflamma-

tion and endothelial dysfunction and reduce paraoxonase

activity.

These lipid and biochemical effects act synergis-

tically to increase cardiovascular disease risk.

The issue is more complex than indicated by HDL-C. Satu-

rated fat rapidly promotes proinflammatory changes in HDL

without changing HDL-C level.

Thus, as mentioned in our

review, dietary intake of both saturated fatty acids and trans-

fatty acids should be avoided and substituted with intake

of monounsaturated and polyunsaturated fatty acids.

Inder M. Singh, MD, MS

Department of Cardiovascular Medicine

Krannert Institute of Cardiology

Indiana University Medical Center

Indianapolis

Mehdi H. Shishehbor, DO, MPH

shishem@gmail.com

Department of Cardiovascular Medicine

Cleveland Clinic

Cleveland, Ohio

Benjamin J. Ansell, MD

Department of Medicine

David Geffen School of Medicine at UCLA

Los Angeles, California

Financial Disclosures: Dr Ansell reported receiving speaking honoraria from As-

traZeneca, Kos Pharmaceuticals, Merck, and Pfizer; receiving research medication

from Merck and Pfizer in the past; and having equity interest in Bruin Pharma. No

other disclosures were reported.

1. Mensink RP, Zock PL, Kester AD, Katan MB. Effects of dietary fatty acids and

carbohydrates on the ratio of serum total to HDL cholesterol and on serum lipids

and apolipoproteins: a meta-analysis of 60 controlled trials. Am J Clin Nutr.2003;

77(5):1146-1155.

2. Mozaffarian D, Katan MB, Ascherio A, Stampfer MJ, Willett WC. Trans fatty

acids and cardiovascular disease. NEnglJMed.2006;354(15):1601-1613.

3. Nicholls SJ, Lundman P, Harmer JA, et al. Consumption of saturated fat im-

pairs the anti-inflammatory properties of high-density lipoproteins and endothe-

lial function. JAmCollCardiol.2006;48(4):715-720.

CORRECTIONS

Data Error: In the Review article entitled “Data Extraction Errors in Meta-analyses

That Use Standardized Mean Differences” published in the July 25, 2007, issue of

JAMA (2007;298:430-437), Figure 4 included incorrect data. The reported point

estimate and its 95% confidence interval for the meta-analysis standardized mean

differences “−0.74 (−0.98 to −0.49)” for the Edmonds et al article should have

read “−0.77 (−1.26 to −0.28).” The error was caused by a wrong label in the Coch-

rane Library at the time of the study. A meta-analysis was stated to have been

done with a random-effects model; however, it was done with a fixed-effect model.

The Cochrane Library no longer contains this error.

Typographical Errors in Tables: In the Research Letter entitled “Patterns of Preva-

lent Major Chronic Disease Among Older Adults in the United States” published

in the September 12, 2007, issue of JAMA (2007;298[10]:1160-1162), both tables

contained typographical errors. In both tables, the column headings of “Esti-

mated Frequency (!1000)” and “CVA” were erroneously transposed and the brace

under the column head “Disease Pattern, No. of Diseases” should have extended

to include the CVA column. Online versions of this article on the JAMA Web site

were corrected on October 4, 2007.

Unreported Financial Disclosures: In the Original Contribution entitled “Non-

pharmaceutical Interventions Implemented by US Cities During the 1918-1919

Influenza Pandemic” published in the August 8, 2007, issue of JAMA (2007;

298[6]:644-654), financial disclosures were inadvertently not reported. On page

654, under “Financial Disclosures,” the following should appear: “Dr Markel re-

ported having received honoraria for delivering lectures on the social and cultural

history of the 1918-1919 influenza pandemic at academic conferences or collo-

quia presented by Yale University, the US Department of Defense, the RAND Cor-

poration, Columbia University, the US Department of Health and Human Ser-

vices, the Michigan Society for Infection Control and Prevention, University of

Michigan, and Emory University. None of the other authors reported financial dis-

closures.”

Incorrect Affiliation: In the Research Letter entitled “Cardiovascular Response to

aModernRollerCoasterRide”publishedintheAugust15,2007,issueofJAMA

(2007;298[7]:739-741), the affiliations were reversed for 2 authors and 1 au-

thor’s name was listed out of order. Joachim Brade, MSc, is affiliated with the De-

partment of Medical Statistics and Dariusch Haghi, MD, is affiliated with the 1st

Department of Medicine-Cardiology, University Hospital of Mannheim, Mannheim,

Germany. The name for Christian Wolpert, MD, should have been placed last among

the list of author names.

LETTERS

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Discussion

The black plague killed more people, and was estimated to have killed 30% to 60% of Europe's population, but occurred in many waves over many years: https://en.wikipedia.org/wiki/Black_Death In 1918, NYC was considered a world leader in public health, and their rapid response was exemplary. 100 years later, NYC acted too slowly. Positive correlation and the graph shows that longer response times were associated with worse outcomes for cities. There were three big waves of the 1918-1919 pandemic. ![Imgur](https://imgur.com/SH7qohb.jpeg) Source: https://www.cdc.gov/flu/pandemic-resources/1918-commemoration/three-waves.htm ![Imgur](https://imgur.com/XT2mTSD.jpg) Source: https://en.wikipedia.org/wiki/Pandemic_severity_index#cite_note-HHS-1 "In dual-peaked cities, activation of nonpharmaceutical interventions was followed by a diminution of deaths and, typically, when nonpharmaceutical interventions were deactivated, death rates increased." This is the risk that cities/states will face if they reopen society, lifting quarantine restrictions too soon. Source: "Pandemics Depress the Economy, Public Health Interventions Do Not: Evidence from the 1918 Flu" The major reason to reopen prematurely is to reactivate the economy and get people back to work. However, a recent economic study analyzing the 1918 pandemic found that cities that kept their restrictions in place longer, experienced greater economic growth following the pandemic. ![Imgur](https://imgur.com/8ieRzXL.jpeg) “History is not a predictive science. There exist numerous well-documented and vast differences between US society and public health during the 1918 pandemic compared with the present. We acknowledge the inherent difficulties of interpreting data recorded nearly 90 years ago and contending with the gaps, omissions, and errors that may be included in the extant historical record.” Important limitation is that 1918 was a long time ago and history doesn’t always repeat itself. "One compelling question emerges: can lessons from the 1918-1919 pandemic be applied to contemporary pandemic planning efforts to maximize public health benefit while minimizing the disruptive social consequences of the pandemic as well as those accompanying public health response measures?" Yes. And we are seeing that firsthand with the NPI measures taken for COVID. "These findings contrast with the conventional wisdom that the 1918 pandemic rapidly spread through each community killing everyone in its path. Although these urban communities had neither effective vaccines nor antivirals, cities that were able to organize and execute a suite of classic public health interventions before the pandemic swept fully through the city appeared to have an associate mitigated epidemic experience." This is the hope with the mitigation strategies now being employed throughout the world for COVID. "Our study suggests that nonpharmaceutical interventions can play a critical role in mitigating the consequences of future severe influenza pandemics (category 4 and 5) and should be considered for inclusion in contemporary planning efforts as companion measures to developing effective vaccines and medications for prophylaxis and treatment. The history of US epidemics also cautions that the public’s acceptance of these health measures is enhanced when guided by ethical and humane principles." This study, and all of the interventions discussed, are directly applicable to our current situation. Even though at the time of the 1918-1919 pandemic, viruses had not been discovered yet, vaccines did not exist, and the common treatments were enemas, bloodletting and leeches, we are in a very similar boat in 2020 until we have a vaccine and effective antiviral treatments. NPIs are the way we deal with this during the mitigation phase.

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