BACKGROUND: Mexico's local and national authorities initiated an intense public health response during the early stages of the 2009 A/H1N1 pandemic. In this study we analyzed the epidemiological patterns of the pandemic during April-December 2009 in Mexico and evaluated the impact of nonmedical interventions, school cycles, and demographic factors on influenza transmission. METHODS AND FINDINGS: We used influenza surveillance data compiled by the Mexican Institute for Social Security, representing 40% of the population, to study patterns in influenza-like illness (ILIs) hospitalizations, deaths, and case-fatality rate by pandemic wave and geographical region. We also estimated the reproduction number (R) on the basis of the growth rate of daily cases, and used a transmission model to evaluate the effectiveness of mitigation strategies initiated during the spring pandemic wave. A total of 117,626 ILI cases were identified during April-December 2009, of which 30.6% were tested for influenza, and 23.3% were positive for the influenza A/H1N1 pandemic virus. A three-wave pandemic profile was identified, with an initial wave in April-May (Mexico City area), a second wave in June-July (southeastern states), and a geographically widespread third wave in August-December. The median age of laboratory confirmed ILI cases was ∼ 18 years overall and increased to ∼ 31 years during autumn (p<0.0001). The case-fatality ratio among ILI cases was 1.2% overall, and highest (5.5%) among people over 60 years. The regional R estimates were 1.8-2.1, 1.6-1.9, and 1.2-1.3 for the spring, summer, and fall waves, respectively. We estimate that the 18-day period of mandatory school closures and other social distancing measures implemented in the greater Mexico City area was associated with a 29%-37% reduction in influenza transmission in spring 2009. In addition, an increase in R was observed in late May and early June in the southeast states, after mandatory school suspension resumed and before summer vacation started. State-specific fall pandemic waves began 2-5 weeks after school reopened for the fall term, coinciding with an age shift in influenza cases. CONCLUSIONS: We documented three spatially heterogeneous waves of the 2009 A/H1N1 pandemic virus in Mexico, which were characterized by a relatively young age distribution of cases. Our study highlights the importance of school cycles on the transmission dynamics of this pandemic influenza strain and suggests that school closure and other mitigation measures could be useful to mitigate future influenza pandemics. Please see later in the article for the Editors' Summary.
BACKGROUND: Mexico's local and national authorities initiated an intense public health response during the early stages of the 2009 A/H1N1 pandemic. In this study we analyzed the epidemiological patterns of the pandemic during April-December 2009 in Mexico and evaluated the impact of nonmedical interventions, school cycles, and demographic factors on influenza transmission. METHODS AND FINDINGS: We used influenza surveillance data compiled by the Mexican Institute for Social Security, representing 40% of the population, to study patterns in influenza-like illness (ILIs) hospitalizations, deaths, and case-fatality rate by pandemic wave and geographical region. We also estimated the reproduction number (R) on the basis of the growth rate of daily cases, and used a transmission model to evaluate the effectiveness of mitigation strategies initiated during the spring pandemic wave. A total of 117,626 ILI cases were identified during April-December 2009, of which 30.6% were tested for influenza, and 23.3% were positive for the influenzaA/H1N1 pandemic virus. A three-wave pandemic profile was identified, with an initial wave in April-May (Mexico City area), a second wave in June-July (southeastern states), and a geographically widespread third wave in August-December. The median age of laboratory confirmed ILI cases was ∼ 18 years overall and increased to ∼ 31 years during autumn (p<0.0001). The case-fatality ratio among ILI cases was 1.2% overall, and highest (5.5%) among people over 60 years. The regional R estimates were 1.8-2.1, 1.6-1.9, and 1.2-1.3 for the spring, summer, and fall waves, respectively. We estimate that the 18-day period of mandatory school closures and other social distancing measures implemented in the greater Mexico City area was associated with a 29%-37% reduction in influenza transmission in spring 2009. In addition, an increase in R was observed in late May and early June in the southeast states, after mandatory school suspension resumed and before summer vacation started. State-specific fall pandemic waves began 2-5 weeks after school reopened for the fall term, coinciding with an age shift in influenza cases. CONCLUSIONS: We documented three spatially heterogeneous waves of the 2009 A/H1N1 pandemic virus in Mexico, which were characterized by a relatively young age distribution of cases. Our study highlights the importance of school cycles on the transmission dynamics of this pandemic influenza strain and suggests that school closure and other mitigation measures could be useful to mitigate future influenza pandemics. Please see later in the article for the Editors' Summary.
In late March and early April 2009, reports of respiratory hospitalizations and
deaths among young adults in Mexico alerted local health officials to the occurrence
of atypical rates of respiratory illness at a time when influenza was not expected
to reach epidemic levels [1]–[3]. Infections with novel swine-origin influenzaA/H1N1 virus
were confirmed in California, (United States), on April 21 [4] and in Mexico on April 23 [5]. The Ministry
of Health cancelled educational activities in the greater Mexico City area on April
24 and expanded these measures to the rest of the country on April 27 [6].
Additional social distancing interventions were implemented in the greater Mexico
City area, including the closure of movie theaters and restaurants and the
cancellation of large public gatherings (Table 1) [6]. Schools reopened on
May 11 and remained in session until the scheduled summer vacation period, which
began in July 2009. Whether these intense interventions were successful in reducing
disease transmission has yet to be evaluated, which is important for the control of
future pandemics [7].
Table 1
Timeline of events relevant to the detection, control, and school
activity periods during the 2009 A/H1N1 influenza pandemic in
Mexico.
Dates
Events
April 5–18, 2009
Spring break school vacation period for approximately
34 million students from elementary to university levels.
April 12, 2009
Mexico reports an outbreak of respiratory disease to
the Pan-American Health Organization (PAHO)
April 17, 2009
Ministry of Health issues epidemiologic alert
April, 23 2009
The Public Health Agency of Canada confirms cases of
novel swine-origin (A/H1N1) influenza virus
April 24–May 11, 2009
Educational activities at all levels are cancelled in
the Federal District (Distrito Federal) and the metropolitan area,
including the state of Mexico. Movie theaters, restaurants, soccer
stadiums, and churches are also temporarily closed in the greater
Mexico City metropolitan area
April 27–May 11, 2009
School closures are extended to the rest of the
country
July 3, 2009
Summer school vacation period begins
August 10, 2009
Start of the school term for university students
August 24, 2009
Start of the school term for public primary and
secondary schools
December 22, 2009
Winter school vacation period begins
Increasing our understanding of the age and transmission patterns of the 2009 A/H1N1influenza pandemic at various geographic scales is crucial for designing more
efficient public health interventions against future influenza pandemics.
Spatio-temporal variations in influenza transmission can result from variation in
population contact rates linked to school cycles or intervention strategies, as well
as the timing of a virus's introduction relative to climatic conditions and
prior population immunity (e.g., [8],[9]). While variation in the transmission potential and the
timing of the spring waves of the 2009 A/H1N1 pandemic have been reported in several
countries (e.g., [10]–[16]), there have been no studies thus far concentrating on
recurrent pandemic waves in Mexico, one of the countries affected earliest by the
2009 A/H1N1influenza pandemic. Here, we analyze the age- and state-specific
incidence of influenza morbidity and mortality in 32 Mexican States, on the basis of
reports to the Mexican Institute for Social Security (IMSS), a private medical
system that covers 40% of the Mexican population. We also quantify the
association between local influenza transmission rates, school cycles, and
demographic factors.
Methods
Epidemiological and Population Data
We relied on the epidemiological surveillance system of IMSS, described in detail
by Echevarria-Zuno et al. [17]. IMSS is a
tripartite Mexican health system covering workers in the private sector and
their families, a group that comprises roughly 40% of the Mexican
population (107 million individuals), with a network of 1,099 primary health
care units and 259 hospitals nationwide. Overall, the age distribution of the
population affiliated with IMSS is representative of the general population of
Mexico (chi-square test, p = 0.18) (Text S1,
figure A) [18]. The male-to-female ratio among the population affiliated
with IMSS (47:53) is similar to that of the general population (49:51).Active surveillance for severe pneumonia started at all IMSS hospitals after a
first epidemiological alert was issued on April 17, 2009. On April 28 the
surveillance system was expanded to include influenza-like illness (ILI)
patients visiting primary health care units and hospitals as well as
influenza-related deaths. Patient information was entered into an online
surveillance system by hospital or clinic epidemiologists. ILI was defined as a
combination of cough, headache, and fever (except for persons over 65 y) with
one or more of the following symptoms: sore throat, rhinorrhea, arthralgias,
myalgia, prostration, thoracic pain, abdominal pain, nasal congestion, diarrhea,
and irritability (for infants only) [17]. Respiratory swabs
were obtained for about a third of cases with constant sampling intensity across
states, time, and age groups (Text S1, figures B and C and table A). Swabs
were tested for A/H1N1influenza virus by real-time reverse transcription PCR
[19] by
the Instituto de Diagnóstico y Referencia Epidemiológica (InDRE)
until May 25, 2009, after which point samples were analyzed by La Raza, an IMSS
laboratory certified by InDRE [17].We obtained patient age, date of symptom onset, disease outcome (inpatient,
outpatient, and death), and reporting state (including 31 states plus the
Federal District, which we collectively refer to as “32 states” for
simplicity) for ILI and laboratory-confirmed A/H1N1 pandemic influenza cases
reported between April 1 and December 31, 2009. We also obtained population data
by state and age group for all persons affiliated with IMSS in 2009 to calculate
incidence rates.
Spatial Distribution of Pandemic Waves
We compiled state- and age-specific time series of incident ILI and A/H1N1
pandemic influenza cases by day of symptom onset to analyze the geographic
spread of the pandemic across Mexico. We defined three temporally distinct
pandemic waves in the spring (April 1–May 20), summer (May 21–August
1), and fall (August 2–December 31) of 2009 on the basis of patterns in
national A/H1N1influenza incidence time series (Figure 1). For each state and pandemic wave,
we recorded the cumulative number of cases, cumulative incidence rate, and peak
date, defined as the day with the maximum number of new cases.
Figure 1
Daily number of laboratory-confirmed A/H1N1 pandemic influenza cases
from April 1 to December 31, 2009 in the 32 Mexican states sorted by
distance from Mexico City.
For visualization purposes, the time series are log-transformed.
Daily number of laboratory-confirmed A/H1N1 pandemic influenza cases
from April 1 to December 31, 2009 in the 32 Mexican states sorted by
distance from Mexico City.
For visualization purposes, the time series are log-transformed.We also explored geographic variation in the timing of pandemic onset across
states and its association with the start of the fall school term, population
size, population density, and distance from Mexico City. For each pandemic wave
and Mexican state, the onset day was defined as the first day of the period of
monotonously increasing cases leading up to the peak of A/H1N1 cases, as in
[20].
Age Distribution of Influenza Cases and Deaths
We examined the age distribution of ILI and A/H1N1 pandemic influenza cases by
geographic region and over time, using weekly rather than daily case time series
in order to avoid low case counts at the beginning and end of each pandemic
wave. We also estimated age-specific measures of disease severity including the
case-fatality ratio (CFR = deaths/cases, where numerators
and denominators can be based on ILI or laboratory-confirmed cases).
Estimation of Transmission Potential
We estimated the reproduction number, R, for each pandemic wave and geographic
region of Mexico (north, central, and southeast). We used a simple method that
relies on the estimation of the growth rate by fitting an exponential function
to the early ascending phase of daily A/H1N1 pandemic cases, where the epidemic
curve is based on symptoms onset (Text S1 and [20]–[23]). The
early ascending phase was determined as the period between the day of pandemic
onset (as defined above) and the midpoint between the onset and peak days, for
each regional pandemic wave. We assumed a mean generation interval of 3 and 4 d,
which are within the range of mean estimates for the 2009 A/H1N1influenza
pandemic [11],[13],[24],[25].We assessed the sensitivity of our estimates to small variations in the
definition of the ascending phase used to estimate the exponential growth rate
(±4 d). Because variability in daily testing rates could affect R
estimates derived from A/H1N1 time series, particularly during the early phase
of the spring wave, we conducted a sensitivity analysis using ILI time
series.
Impact of School Closures during the 2009 Spring Wave
School activities have been linked with increased influenza transmission rates in
both pandemic and interpandemic periods [26]–[29]. We assessed the
effectiveness of mandatory school closures and other social distancing measures
implemented during April 24–May 11, 2009 in the central region of Mexico
in reducing influenza transmission rates. We fitted a mathematical model of
influenza transmission to daily case data (Text S1).
This approach allows estimation of separate influenza transmission rates for the
periods before and during intervention and explicitly accounts for the depletion
of susceptible individuals.In addition, to analyze changes in the age distribution of cases with school
activity periods, we computed the daily ratio of incident A/H1N1 pandemic cases
among the student population (5–20 y) to cases among other age groups.
Results
General Description of the Three Pandemic Waves in Mexico
A total of 117,626 ILI cases were reported by IMSS from April 1 to December 31,
2009, of which 36,044 were laboratory tested (30.6%) and 27,440
(23.3%) were confirmed with A/H1N1 pandemic influenza. A total of 1,370
ILI deaths (3.6 per 100,000) were reported to the surveillance system, of which
585 (1.5 per 100,000) were confirmed with A/H1N1 pandemic influenza. There was
no significant trend in testing rates by geographic region or age group, and
testing remained constant over time, except for a rapid increase during the
first 2–3 wk of the pandemic (Text S1 and figures B–E therein).The spatial-temporal distribution of A/H1N1 pandemic influenza and ILI cases
reveal a three-wave pattern in the spring, summer, and fall of 2009 with
substantial geographical clustering (Figures 1–
3). The spring pandemic wave in April–May 2009 was mainly
confined to the greater Mexico City area and other central states. The summer
wave in June 2009 was limited to southern states, and ended soon after the start
of the summer school vacation period on July 3, 2009. A third wave of widespread
activity began in August 2009, coinciding with the return of students from
summer vacations, and disease activity persisted until December 2009 throughout
Mexico.
Figure 2
Daily epidemic curve in northern, central, and southeastern states of
Mexico, April 1 to December 31, 2009, based on laboratory-confirmed
A/H1N1 pandemic influenza cases.
Figure 3
Maps of laboratory-confirmed A/H1N1 pandemic cases across Mexican
states for the entire study period, April–December 2009, and by
pandemic wave.
The spring wave (April 1–May 20) was focused on the central region,
including the state of Mexico, Distrito Federal, Jalisco, Puebla, San
Luis Potosi, Guerrero, Hidalgo, and Tlaxcala. The summer wave (May
21–August 1) was concentrated in the southeast states of Veracruz,
Yucatan, Quintana Roo, Chiapas, Oaxaca, Tabasco, and Campeche. The fall
wave (August 2–December 31) affected the central region and the
northern states of Baja California Norte, Sonora, Chihuahua, Coahuila,
Nuevo Leon, and Tamaulipas. For each pandemic wave, the color scale
range was set according to the highest number of cases across
states.
Maps of laboratory-confirmed A/H1N1 pandemic cases across Mexican
states for the entire study period, April–December 2009, and by
pandemic wave.
The spring wave (April 1–May 20) was focused on the central region,
including the state of Mexico, Distrito Federal, Jalisco, Puebla, San
Luis Potosi, Guerrero, Hidalgo, and Tlaxcala. The summer wave (May
21–August 1) was concentrated in the southeast states of Veracruz,
Yucatan, Quintana Roo, Chiapas, Oaxaca, Tabasco, and Campeche. The fall
wave (August 2–December 31) affected the central region and the
northern states of Baja California Norte, Sonora, Chihuahua, Coahuila,
Nuevo Leon, and Tamaulipas. For each pandemic wave, the color scale
range was set according to the highest number of cases across
states.The average cumulative incidence rate of pandemic A/H1N1 was 16.6 per 100,000
across the 32 states (95% confidence interval [CI]
16.2–17.0) in spring-summer and 55.7 per 100,000 (95% CI
55.0–56.5) in the fall. Most states experienced highest disease rates in
the fall, except for five southeastern states (Figure 3). Similar spatial and temporal
patterns were observed in hospitalization and mortality time series (Text S1,
figure F).
Age Patterns of Cases and Disease Severity
The median age of A/H1N1 cases was 18 y (range, 0–99 y). H1N1 morbidity
rate was highest among children 5–14 y (115.7 per 100,000) and lowest
among seniors 60 y and older (9.2 per 100,000, Table 2; Text S1,
figure G). The age-specific risk of severe disease was J-shaped, with highest
case-fatality and case-hospitalization rates in people older than 60 y, and
relatively high rates in infants (Table 3). The overall CFR was estimated at 1.2% (95%
CI 1.1–1.2) on the basis of ILI cases and deaths and 5% (95%
CI 4.7–5.3) on the basis of laboratory-confirmed A/H1N1 cases and deaths.
The ILI CFR varied geographically and was estimated at 0.5% (95%
CI 0.4–0.5) in the southeastern region, 1.0% (95% CI
0.9–1.1) in the northern region, and 1.9% (95% CI
1.8–2.1) in the central region.
Table 2
Distribution of age-specific laboratory-confirmed 2009 A/H1N1
pandemic influenza morbidity rates by geographic region in Mexico, April
1–December 31, 2009.
Age (y)
Mexico
Central States
Northern States
Southeastern States
Total
Incidence per 100,000
Total
Incidence per 100,000
Total
Incidence per 100,000
Total
Incidence per 100,000
Total n
27,440
72.2
10,976
71.1
4,484
44.1
6,115
126.7
0–4
3,600
112.7
1,267
106.9
677
72.4
904
235.3
5–14
7,988
115.7
3,254
121.8
1,236
62.8
1,817
226.4
15–29
8,699
115.4
3,356
112.1
1,412
72.2
2,010
192.7
30–44
4,275
48.6
1,804
50.5
684
28.1
857
77.0
45–59
2,340
41.0
1,052
42.8
386
26.7
431
59.1
≥60
538
9.2
243
9.5
89
6.2
96
12.7
Mean ± SD
21.2 ± 16.0
—
22.0 ± 16.3
—
21.0 ± 16.2
—
20.0 ± 15.3
—
Median [range]
18 [0–99]
—
19 [0–99]
—
18 [0–89]
—
17 [0–97]
—
We note a slight but significant difference in the age distribution
of cases between regions (Wilcoxon test,
p<0.009).
SD, standard deviation.
Table 3
Age-specific 2009 A/H1N1 pandemic influenza severity estimates in
Mexico, April 1–December 31, 2009.
Age (y)
ILI Cases Hospitalized for Severe Acute
Respiratory Infection
Laboratory-Confirmed A/H1N1 Hospitalizations n
(A/H1N1 Admission Ratea)
ILI Deaths n(Mortality Ratea)
Confirmed A/H1N1 Admissions (95% CI)b
ILI CFR (95% CI)c
Confirmed A/H1N1 CFR (95% CI)d
Confirmed A/H1N1 Death Rate among Hospitalized
Cases (95% CI)e
n
Percent of Total ILI Cases
Total
11,706
10.0 (9.8–10.1)
3,402 (9.0)
1,370 (3.6)
12.4 (12.0–12.8)
1.2 (1.1–1.2)
5.0 (4.7–5.3)
17.2 (15.9–18.5)
0–4
2,399
13.3 (12.8–13.8)
434 (13.6)
109 (3.4)
12.1 (11.0–13.2)
0.6 (0.5–0.7)
3.0 (2.5–3.6)
11.3 (8.3–14.3)
5–14
1,523
5.2 (5.0–5.5)
600 (8.7)
68 (1.0)
7.5 (6.9–8.1)
0.2 (0.2–0.3)
0.9 (0.7–1.1)
5.3 (3.5–7.2)
15–29
2,580
7.4 (7.1–7.7)
992 (13.2)
228 (3.0)
11.4 (10.7–12.1)
0.7 (0.6–0.7)
2.6 (2.3–3.0)
12.6 (10.5–14.7)
30–44
2,277
10.8 (10.4–11.3)
655 (7.4)
383 (4.4)
15.3 (14.2–16.4)
1.8 (1.6–2.0)
9.0 (8.1–9.8)
26.6 (23.1–30.0)
45–59
1,744
16.3 (15.6–17.0)
530 (9.3)
371 (6.5)
22.6 (20.9–24.4)
3.5 (3.1–3.8)
15.8 (14.3–17.3)
28.5 (24.6–32.4)
≥60
1,183
30.6 (29.1–32.1)
191 (3.3)
211 (3.6)
35.5 (31.4–39.6)
5.5 (4.7–6.2)
39.2 (35.0–43.4)
28.3 (21.2–34.8)
Per 100,000 people affiliated to IMSS.
(Admitted to hospital with confirmed H1N1/total confirmed H1N1) *
100.
(Deaths/ILI) *100.
(H1N1 deaths/ H1N1 cases) *100.
(H1N1 deaths/H1N1 hospitalizations) *100.
We note a slight but significant difference in the age distribution
of cases between regions (Wilcoxon test,
p<0.009).SD, standard deviation.Per 100,000 people affiliated to IMSS.(Admitted to hospital with confirmed H1N1/total confirmed H1N1) *
100.(Deaths/ILI) *100.(H1N1 deaths/ H1N1 cases) *100.(H1N1 deaths/H1N1 hospitalizations) *100.Cumulative rates of A/H1N1 followed a similar age profile across all regions,
with peak morbidity rates in the age range of 0–14 y and a consistent drop
in morbidity rates after age 30 (Table 2). There was a trend towards increasing age as the fall wave
progressed (September 9–December 31; regression against time
R
2 = 0.94,
p<0.0001), with the median age reaching ∼31 y in
December 2009 (Text S1, figure H). There was a similar trend in ILI cases
(R
2 = 0.94,
p<0.0001), laboratory-confirmed hospitalized cases
(R2 = 0.62,
p = 0.0002), and laboratory-confirmed
deaths (R
2 = 0.26,
p = 0.04).
Demographic Factors and Variation in Timing and Magnitude of the
Pandemic
Next we explored whether demographic factors may partly explain the observed
variation in timing of onset and magnitude of the three pandemic pandemic waves
across the 32 Mexican states. First, we tested the association between the
incidences of successive waves, which could reflect the gradual build-up of
immunity (and thus, negative association) or the impact of baseline
sociodemographic factors (positive association). Cumulative incidence rates had
a weak positive correlation between spring and fall (Spearman rho for A/H1N1
rates = 0.4,
p = 0.046), but there was no significant
correlation between the summer wave and the spring or fall waves
(p>0.16).The total morbidity burden of the pandemic, measured as the cumulative A/H1N1
incidence rate during April–December 2009, was negatively correlated with
population size (Spearman rho = −0.58,
p<0.001, Text S1 and figure I therein). We found a
similar correlation with ILI rates and rates of IMSS-affiliated individuals
tested for influenza (Spearman rho = −0.4,
p = 0.02, and
rho = −0.61, p<0.001,
respectively) and the association remained after adjustment for population
structure. These findings suggest that low population areas reported higher
pandemic morbidity rates than large population centers and that the association
was not an artifact of testing practices or population age structure. In
contrast, we did not find any association between pandemic morbidity rates and
population density. Further, rates of hospitalization and death were not
correlated with population size or density (p>0.15).Population size was also associated with the onset of the fall pandemic wave,
with earlier onset occurring in more populous states (Spearman
rho = −0.60,
p = 0.003; Text S1,
figure J); however, there was no association between onset and population
density (rho = −0.032,
p = 0.13), distance from Mexico City
(rho = 0.02,
p = 0.92), or the onset of earlier waves
(Text
S1).
Trends in Reproduction Number (R) and Impact of School Closure
We estimated the mean R for the spring, summer, and fall waves in three
geographic regions based on confirmed H1N1 cases (Table 4; Text S1,
figure K). Assuming a mean generation interval of 3 (and 4) d, the mean R was
estimated to be 1.8 (2.1) for the spring wave in the central region prior to the
national school closure period, 1.6 (1.9) for the summer wave in the southeast
region, and 1.2 (1.3) for the fall wave in both central and northern regions. R
estimates obtained from ILI cases were 13%–17% lower than
those obtained from confirmed cases for the spring and summer waves, while there
was no difference for the fall wave. There was little variation in R estimates
when we increased or shortened the growth rate period by 4 d (difference of
0.1–0.2 for the spring and summer waves and 0.1 or less for the fall
wave). An upper bound for R is provided in Text S1,
table B, with the extreme case of a fixed generation interval, and suggests that
R remained below 2.5 throughout the pandemic in Mexico.
Table 4
Mean estimates of the reproduction number and corresponding
95% CIs for the spring, summer, and fall waves of the 2009 A/H1N1
influenza pandemic by geographic region.
Pandemic Wave
Geographic Region
Central States
Southeastern States
Northern States
3-d Serial Interval
4-d Serial Interval
3-d Serial Interval
4-d Serial Interval
3-d Serial Interval
4-d Serial Interval
Spring
1.80 (1.78–1.81)
2.12 (2.09–2.14)
—
—
—
—
Summer
—
—
1.62 (1.61–1.63)
1.85 (1.84–1.87)
—
—
Fall
1.23 (1.22–1.23)
1.31 (1.30–1.31)
—
—
1.24 (1.23–1.24)
1.32 (1.31–1.32)
The latent and infectious periods are assumed to be exponentially
distributed with a serial interval of 3 and 4 d. The epidemic growth
phase used to estimate the R consisted of 14 d for the spring wave
(April 12–April 25) and summer wave (May 21–June 3) and
28 d for the fall wave in central states (August 5–September
1) and northern states (August 8–September 4).
See Text S1, figure K, for exact time periods considered as
part of the epidemic growth phase.
The latent and infectious periods are assumed to be exponentially
distributed with a serial interval of 3 and 4 d. The epidemic growth
phase used to estimate the R consisted of 14 d for the spring wave
(April 12–April 25) and summer wave (May 21–June 3) and
28 d for the fall wave in central states (August 5–September
1) and northern states (August 8–September 4).See Text S1, figure K, for exact time periods considered as
part of the epidemic growth phase.We identified significant changes in the R during the spring wave according to
school activity periods (Figure 4A
and 4B). Focusing on central states affected by a substantial spring
wave, we estimate that R increased from 1.3 (95% CI 1.2–1.5) to 2.2
(95% CI 1.4, 3.1) after the end of the spring break vacation period. A
decrease in R from 2.2 (95% CI 1.4–3.1) to 1.0 (95% CI
0.94–1.06) coincided with the suspension of educational activities and the
implementation of other social distancing measures enforced between April 24 and
May 11, 2009. To explicitly account for the effects of depletion of susceptible
individuals, we fitted a transmission model to daily influenzaH1N1 case data
and quantified the relative change in mean transmission rate during the
intervention period. We estimated that the transmission rate was reduced by
29.6% (95% CI 28.9%–30.2%) during the
intervention period (Figure
5). Our model gave a good fit to the spring epidemic curve overall,
although it yielded a slightly higher number of cases than observed until the
last week of April (chi-square test, bins = 41,
df = 37, p = 0.22,
Figure 5). As a
sensitivity analysis, we also fitted the model to ILI cases and found a
reduction of 36.2% (95% CI 35.9%–36.5%)
associated with social distancing measures.
Figure 4
Trends in influenza pandemic patterns and school activities.
(A) H1N1 cases, natural scale; (B) H1N1 cases, log-scale, (C) testing
rates (n tests/n ILI), and (D)
proportion of hospitalizations among ILI cases during the spring
pandemic wave in central Mexico in 2009. Shaded areas denote periods
when schools are not in session, including during the spring break
(April 4–18) and the mandatory suspension of educational
activities (April 24–May 11). (B) indicates changes in the R
estimates over time, as measured from the exponential growth rate of the
incidence curves.
Figure 5
Fit of influenza transmission model to the daily number of H1N1
pandemic influenza cases in central Mexico, April 1–May 11,
2009.
The grey shaded area indicates the suspension of educational activities
and other social distancing measures implemented between April 24 and
May 11, 2009. Black circles represent the observed data. The solid red
line is the model best-fit, and the blue lines are CIs based on 100
realizations of the model obtained by parametric bootstrapping (Text
S1).
Trends in influenza pandemic patterns and school activities.
(A) H1N1 cases, natural scale; (B) H1N1 cases, log-scale, (C) testing
rates (n tests/n ILI), and (D)
proportion of hospitalizations among ILI cases during the spring
pandemic wave in central Mexico in 2009. Shaded areas denote periods
when schools are not in session, including during the spring break
(April 4–18) and the mandatory suspension of educational
activities (April 24–May 11). (B) indicates changes in the R
estimates over time, as measured from the exponential growth rate of the
incidence curves.
Fit of influenza transmission model to the daily number of H1N1
pandemic influenza cases in central Mexico, April 1–May 11,
2009.
The grey shaded area indicates the suspension of educational activities
and other social distancing measures implemented between April 24 and
May 11, 2009. Black circles represent the observed data. The solid red
line is the model best-fit, and the blue lines are CIs based on 100
realizations of the model obtained by parametric bootstrapping (Text
S1).To further test the impact of school cycles, we monitored trends in the ratio of
incident student to nonstudent influenzaA/H1N1 cases. At the national scale,
this ratio was low during the summer vacations and increased sharply following
the start of school activities in August (Wilcoxon test,
p<0.001, Figure
6). At the state level, the ratio of student to nonstudent cases
peaked 2–5 wk after schools reopened in the fall of 2009
(Text
S1, figures L–M).
Figure 6
Changes in the age distribution of cases during the summer and fall
pandemic waves in Mexico.
(A) Weekly time series of laboratory-confirmed A/H1N1 pandemic cases
among students (5–20 y, red curve) and other age
groups (blue curve) and (B) Weekly ratio of student to nonstudent A/H1N1
cases. The grey shaded area indicates the mandatory school closure
period (April 24–May 11) and the summer vacation
period (July 3–August 23) for elementary and
secondary school students. College students retuned to class on August
10th(arrow).
Changes in the age distribution of cases during the summer and fall
pandemic waves in Mexico.
(A) Weekly time series of laboratory-confirmed A/H1N1 pandemic cases
among students (5–20 y, red curve) and other age
groups (blue curve) and (B) Weekly ratio of student to nonstudent A/H1N1
cases. The grey shaded area indicates the mandatory school closure
period (April 24–May 11) and the summer vacation
period (July 3–August 23) for elementary and
secondary school students. College students retuned to class on August
10th(arrow).
Discussion
This is, to our knowledge, the first study to explore spatio-temporal variation in
the dynamics and age patterns of the 2009 A/H1N1 pandemic in Mexico, relying on a
large sample of laboratory-confirmed and ILI data collected by a private medical
system representing a population of over 100 million people. Our findings support
the effectiveness of early mitigation efforts in the greater Mexico City area in the
spring of 2009, including mandatory school closures and cancellation of large public
gatherings. In addition, the onset of the fall pandemic wave in Mexico coincided
with the start of the fall term in schools and universities, reinforcing the
importance of school cycles in the transmission of pandemic influenza. Our data also
reveal substantial geographical variation in pandemic patterns across Mexico, in
part related to population size, with three consecutive waves of varying amplitude
occurring over an 8-mo period. In line with previous studies [–[, we
note that the age distribution of pandemic influenza morbidity was highly skewed
towards younger age groups (median 18 y), while the risk of severe disease was
skewed towards older age groups. Of note was the particularly high CFR reported in
these Mexican data (CFR≈1% based on the ratio of ILI deaths to ILI
cases).Our transmission model fitted to daily case data suggests that the 18-d period of
mandatory school closure and cancellation of public gathering in the greater Mexico
area was associated with a 29%–37% reduction in the
transmission of pandemic influenza. Overall, our estimates are in agreement with a
recent study suggesting an ∼25% reduction in A/H1N1 transmission
following secondary schools closures in Hong Kong from June 11 to July 10, 2009
[33]. Similarly, a
European study of variation in contact rate patterns suggested a
13%–40% reduction in reproduction number with
holiday periods in Belgium, Great Britain, and The Netherlands [34]. In our data, the resurgence of
influenza activity within 2–5 wk of the beginning of fall term in
the 32 Mexican states, together with a rapid change in the age distribution of cases
around this time, further suggests the importance of school cycles for pandemic
influenza transmission. Accordingly, previous studies have shown a temporal
association between school cycles and the onsets of the fall 1957 and 2009 pandemic
waves in the US [28],[35],[36].While past studies have concentrated on R estimates for the spring wave in Mexico and
other countries, this is the first study, to our knowledge, to provide estimates for
all three pandemic waves in any country. Our estimates were highest for the spring
wave (R≈1.8–2.1), declined in the summer
(R≈1.6–1.9), and were lowest in the fall
(R≈1.2–1.3). The significantly lower fall estimates may be
explained by higher levels of herd immunity and preventive measures put in place in
preparation for the start of school term. These included cleaning and disinfection
of schools, promotion of hand hygiene, and screening and management of incident ILI
cases among students and school staff.Our R estimates were robust to small variation in the definition of the epidemic
ascending phase and the use of confirmed H1N1 or ILI cases, which rules out
potential biases due to testing practices. Overall our spring R estimates are in
line with previous studies focusing on the early pandemic phase in Mexico, with
estimates ranging between 1.4–2.4 [11],[37],[38]. In other countries, R was
estimated at 1.2–2.4 for community-based settings in Japan [39], New Zealand
[40], Australia
[41], Peru
[42], Chile
[43],
Ontario, Canada [44], and the US [45], while higher estimates in the
range 2.3–3.3 were obtained during school outbreaks [13],[14],[46]. The variability in published
R estimates of the first wave of the 2009 pandemic could be attributed to
differences in control strategies, school activity periods, travel patterns, and
climatic conditions [8],[9], which should be more fully investigated.The number and intensity of the 2009 H1N1 pandemic waves varied substantially across
regions of the world. While Mexico, the US, and the UK experienced a
“herald” pandemic wave in the spring of 2009 followed by one or more
waves during the summer and fall 2009 [10],[12],[47], a number of countries, particularly in the Southern
Hemisphere, have experienced only a single pandemic wave in 2009, including Chile
[48],
Argentina [49],
Australia [50],[51], and New Zealand [50]. Other countries in Europe also
experienced a single main wave in the fall of 2009 [16], followed by a recrudescence
of H1N1 activity more than one year later in winter 2010–2011. Our detailed
analysis of 2009 pandemic patterns in Mexican states suggests that all of these
configurations were observed within Mexico. Similarly, past influenza pandemics have
exhibited multiple waves over short periods of time, as reported for the 1918
pandemic in Mexico [22] and elsewhere [52]–[54].For reasons that remain unclear, there are substantial spatial variations in the
seasonality of influenza epidemics across Mexican regions in interpandemic years,
which may have played a role in the geographical asynchrony of the 2009 A/H1N1
pandemic. Interpandemic influenza activity has strong winter seasonality in northern
and central Mexico [1], while influenza has been detected between December and
July in the tropical southeast [55]. It is perhaps not
surprising that the Southeast region experienced a large-scale A/H1N1 pandemic wave
in summer 2009 and a relatively minor wave in the fall. While absolute humidity has
been found to be associated with the onset of interpandemic and pandemic influenza
activity in the US [9],[56], we did not identify a correlation with the three-wave
pandemic profile in Mexico (Text S1) [56]. Further analysis of the
environmental or social factors influencing the transmission of interpandemic and
pandemic influenza is warranted in order to fully explain influenza seasonality
patterns [57].We found that spatial variation in the timing and magnitude of the three A/H1N1
pandemic waves across Mexican states was partly linked to population size. Influenza
spread in Mexico was driven by large population centers, reminiscent of seasonal
influenza in the US [58] and the 1918 pandemic in England and Wales [20],[59]. We found
significant spatial heterogeneity in the distribution of incidence rates across
states, with lowest incidence rates observed in large population centers. A similar
protective effect of large population centers was evidenced in the context of the
1918 pandemic in England and Wales [20]. These results could be explained by local differences in
health care seeking behavior or in the effectiveness of social distancing measures
[60].Our large dataset allowed estimation of pandemic disease severity for relatively fine
age groups, which could help identify priority age groups for vaccination and
treatment in future pandemics. Although it may not be possible to extrapolate
findings from this pandemic to the next influenza pandemic, the last four pandemics
have been characterized by significant excess mortality among young adults as well
as significant sparing of older populations [52]. Our case-based severity
estimates derived from hospitalization and death reports were highest among people
older than 60 y, and they were substantially higher than in other countries [32],[61]–[64]. In particular, our
CFR based on ILI visits was estimated at 3% during the spring wave,
0.5% during the summer wave, and 1.2% during the fall wave, while our
ILI-based hospitalization rate was around 10%. This is one to two orders of
magnitude higher than estimates reported in several studies [61],[62],[64] and similar to estimates based on
hospitalization cases series in the spring of 2009 in California and Argentina [63],[65]. Our high
case-based severity estimates likely reflect a bias of the Mexican IMSS influenza
surveillance system towards the higher levels of the severity pyramid [62]. As a
sensitivity analysis, and for comparison with previous studies, we estimated CFR
using 2009 A/H1N1 serological attack rates as denominator. Because of the lack of
serological estimates from Mexico, we used age-specific serological data from the UK
reported for the two waves of the pandemic there (May 2009 to April 2010) [66]. Using UK
data as denominator suggests that the age-adjusted CFR could be in the order of
∼0.01% in Mexico with a pattern of increasing severity with age. This
estimate is two orders of magnitude lower than our CFR based on ILI cases and is in
close agreement with estimates from other countries [61],[62],[64]. Further studies comparing excess
mortality rates derived from vital statistics for different countries and influenza
seasons may shed more light on the relative severity of this pandemic.Several caveats are worth noting in our analysis of the 2009 pandemic in Mexico. We
used data on ILI and laboratory-confirmed influenza cases reported to the Mexican
Institute for Social Security network in 32 states, and there may be sampling
variation between states. However, about one-third of all ILI cases were
consistently tested for influenza in all regions and throughout the main pandemic
period (except for the early spring), and we did not see any evidence of weaker
disease surveillance in smaller states (Text S1). On the contrary, states with lower
population sizes reported more cases proportionally than larger states. The
reduction in R observed during the social distancing period occurred during a period
of increasing testing rates (Figure
4C). One would expect that increasing testing rates would lead to
overestimation of the growth rate in H1N1 cases and may in turn result in
overestimation of the impact of social distancing. Nevertheless, our sensitivity
analyses based on ILI data gave similar results, and we do not think likely that
spatial or temporal differences in ILI rates and health-seeking behavior may bias
these analyses. We cannot rule out, however, the impact of other factors on R
estimates, including a reduction in the delay from symptom onset to hospital
admission in the spring, potentially reducing the effective infectious period (Figure 4D) [17], and the use of 1.2
million doses of oseltamivir for influenza treatment around the time of school
closure.In conclusion, our work suggests that intervention measures initiated in Mexico early
in the pandemic period in April–May 2009 were effective in temporarily
reducing disease transmission and that the start of the fall school term in August
2009 may have facilitated the onset of a widespread pandemic wave. It will be
interesting to formally compare the Mexican experience with that of other locations
that applied similar measures, such as Hong Kong [33]. The heterogeneous Mexican
experience also suggests that it will be relatively difficult to predict the local
impact and transmission dynamics of future influenza pandemics globally. We suggest
that population size and school cycles can account for some of the observed
variability and should be integrated into future pandemic planning scenarios.
Finally, it is important to keep in mind that several post-1918 pandemic waves were
associated with substantial health impact in the Americas [22],[67] and that the majority of
influenza deaths associated with the 1889 pandemic in London occurred 2 y after the
initial wave [68]. Therefore, we must remain vigilant and continue to
monitor the circulation and health burden of the A/H1N1 pandemic virus in the coming
years [69].Spanish translation of the Abstract by GC.(0.01 MB DOCX)Click here for additional data file.Characterizing the epidemiology of the 2009 influenza A/H1N1pandemic in
Mexico: Supplementary information.(0.37 MB PDF)Click here for additional data file.
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