born in 1957 what flu have i been exposed to?
BMC Infect Dis. 2016; 16: 405.
Bloodshed and transmissibility patterns of the 1957 influenza pandemic in Maricopa County, Arizona
April J. Cobos
1School of Homo Development and Social Alter, Arizona State University, Tempe, AZ U.s.
iiSchool of Life Sciences, Arizona Land University, Tempe, AZ United states
iiiBarrett, the Honors College, Arizona State Academy, Tempe, AZ Usa
Clinton G. Nelson
oneSchool of Homo Evolution and Social Change, Arizona State University, Tempe, AZ Us
iiSchool of Life Sciences, Arizona Land University, Tempe, AZ Us
Megan Jehn
1Schoolhouse of Human Evolution and Social Change, Arizona State University, Tempe, AZ USA
Cécile Viboud
4Segmentation of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD USA
Gerardo Chowell
1School of Human Evolution and Social Change, Arizona State University, Tempe, AZ The states
4Partition of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Wellness, Bethesda, MD USA
fiveSchool of Public Health, Georgia State University, Atlanta, GA United states of america
Received 2016 Mar 2; Accepted 2016 Jul 13.
Abstract
Background
While prior studies take quantified the mortality brunt of the 1957 H2N2 flu pandemic at broad geographic regions in the The states, little is known about the pandemic touch at a local level. Here we focus on analyzing the transmissibility and mortality brunt of this pandemic in Arizona, a setting where the dry out climate was promoted as reducing respiratory illness transmission yet tuberculosis prevalence was loftier.
Methods
Using archival decease certificates from 1954 to 1961, nosotros quantified the historic period-specific seasonal patterns, excess-mortality rates, and transmissibility patterns of the 1957 H2N2 pandemic in Maricopa County, Arizona. By applying cyclical Serfling linear regression models to weekly mortality rates, the excess-mortality rates due to respiratory and all-causes were estimated for each age group during the pandemic period. The reproduction number was quantified from weekly information using a simple growth rate method and causeless generation intervals of three and 4 days. Local newspaper articles published during 1957–1958 were also examined.
Results
Excess-mortality rates varied between waves, age groups, and causes of decease, simply overall remained low. From October 1959-June 1960, the most astringent wave of the pandemic, the absolute excess-mortality rate based on respiratory deaths per ten,000 population was 16.59 in the elderly (≥65 years). All other age groups exhibit very low excess-mortality and the typical U-shaped age-blueprint was absent. Withal, the standardized mortality ratio was greatest (4.06) among children and young adolescents (five–14 years) from Oct 1957-March 1958, based on mortality rates of respiratory deaths. Transmissibility was greatest during the same 1957–1958 period, when the hateful reproduction number was estimated at ane.08–ane.11, assuming three- or iv-day generation intervals with exponential or fixed distributions.
Conclusions
Maricopa County exhibited very low mortality impact associated with the 1957 flu pandemic. Understanding the relatively low excess-mortality rates and transmissibility in Maricopa Canton during this historic pandemic may help public health officials gear up for and mitigate future outbreaks of influenza.
Keywords: 1957 flu, H2N2 virus, Asian influenza, Mathematical epidemiology, Mortality rates, Transmissibility, Reproduction number, Maricopa Canton, Arizona
Groundwork
After decades of influenza circulation with relatively low virulence following the 1918 influenza pandemic [1–five], the 1957–58 H2N2 pandemic spread to more than 20 countries in less than 4 months and caused almost 60,000 excess deaths in the Us from September 1957- March 1958 [6–viii]. The 1957 influenza pandemic has been associated with an average respiratory excess death rate of 1.9 per 10,000 during 1957–1959 [9]. Moreover, the impact of this pandemic was moderate relative to the 1918 pandemic, but near 10 times greater than the 2009 A/H1N1 influenza pandemic [9].
With the possible exception of persons older than 67 years, individuals had no prior exposure to the A/H2N2 virus, and therefore had no previous immunity to this virus, resulting in about a quarter of the United States population becoming infected [six, vii]. The widespread effects of recent flu pandemics take emphasized the importance of understanding historical pandemics in order to prepare for and mitigate future outbreaks. A amend understanding of the historic period, seasonal, and transmissibility patterns of previous influenza pandemics may help public wellness officials prepare for challenges that we may face during future flu pandemics. Although past studies have quantified the mortality brunt of the 1957–58 influenza pandemic in the United States [eight, ten–12], trivial is known most the transmission and mortality characteristics of this pandemic at pocket-sized spatial scales. Here nosotros aimed to quantify age-specific mortality rates and transmissibility patterns of the 1957–1958 pandemic in Maricopa Canton using publicly available data comprising a long series of detailed mortality records during 1954–1961.
Originating from the Kweichow province of Prc in late February 1957, the virus induced fever, sore throat, headache, angst, and myalgia [thirteen]. The pandemic reached the United States in late May 1957 and the beginning Asian flu outbreak in the Usa occurred in early June in Newport, Rhode Island [10]. However, the get-go serologically confirmed case of the H2N2 virus in Arizona was non reported until September 23, 1957 [14].
Information technology has previously been reported that the Mountain region of the United states, which included Arizona, did not experience a second moving ridge of loftier mortality in early 1958 [10]. However, there is bear witness for variation in the excess mortality rates and temporal patterns for different cities and states within the same geographic region [10]. By using publicly available archival death certificates from the Arizona Department of Health Services, we set out to quantify the age-specific seasonal patterns, mortality rates, and transmissibility patterns of the pandemic in Maricopa County and compare our local estimates with those previously derived at the national level.
Methods
Geographical setting
Maricopa Canton, in the south-central region of Arizona, is bordered by mountain ranges on the e, westward, and due north and includes a portion of the Sonora Desert. While the weather is generally balmy during the fall, wintertime, and spring, temperatures are oft above 100 °F (37.8 °C) during the summer. However, the humidity levels generally remain depression during the summer months. In mid-summer and early fall, Maricopa County experiences annual monsoons with very heavy rainfall [fifteen]. Although at that place may be indoor crowding, which may lead to increased disease transmission in the hot summertime months and the monsoon season [16], flu epidemics in Maricopa County are most common during the wintertime months. As the influenza virus must overcome various environmental factors in order to survive the ship betwixt hosts, climate can be an important factor in the patterns of influenza epidemics [17]. Cases of influenza typically peak in the winter and this may exist due to depression indoor humidity, cold temperatures, and low solar radiation [16].
Maricopa Canton consists of 25 cities and towns, the largest of which is Phoenix, the land uppercase [xv]. According to the US Census Bureau, the population of Maricopa County was 331,770 in 1950 and 663,510 in 1960. In 1950, Maricopa County fabricated up 44 % of the total Arizona state population and in 1960 this increased to 51 % [eighteen, 19]. Additionally, the expiry rate and incidence of tuberculosis in Arizona were notably the highest in the The states in 1957 [20]. Compared to those who lack tuberculosis infection, patients with tuberculosis are more susceptible to flu infections and more likely to die of influenza, making Maricopa County a peculiarly interesting location to study influenza considering of the relatively high prevalence of tuberculosis in its population during the time period of the influenza pandemic [21, 22].
Sources of data
Using an online database provided by the Arizona Department of Health Services (http://genealogy.az.gov), a total of 36,585 all-crusade archival expiry records of individual deaths that occurred in Maricopa County between January one, 1954 and December eight, 1961 were manually retrieved [23]. Expiry records from 1954–1961 were chosen in order to compare the epidemic period of 1957–1961 with a baseline non-epidemic menstruation during 1954–1956. For each death document, the individual's age at death, gender, exact date of death, and crusade(s) of expiry were recorded from the microfilmed records into a digital spreadsheet. For cause(south) of expiry, but the presence (1) or absenteeism (0) of influenza, pneumonia, bronco-pneumonia, bronchitis, lung congestion, and tuberculosis were recorded in the spreadsheet. Duplicate death records and addendums to certificates were consolidated into one record. Nosotros analyzed three pandemic waves during the 1957–1960 period: Oct 1, 1957-March 31, 1958; October i, 1958-June 30, 1959; and Oct 1, 1959-June xxx, 1960.
We grouped the individuals into 6 age categories (<five, 5–xiv, xv–24, 25–44, 45–64, ≥65 years) and assembled weekly and monthly time series for deaths from respiratory illnesses besides as all-causes. Nosotros chose to use narrow historic period categories to enable greater precision when comparing different age groups besides as more resolution on the specific age groups well-nigh affected by the pandemic. Influenza, pneumonia, bronco-pneumonia, bronchitis, and lung congestion were categorized as respiratory causes of death. It has previously been suggested that the severity of influenza epidemics cannot be fully measured by flu and pneumonia deaths [8, 10, 24]. The magnitude of influenza epidemics is meliorate represented by measuring the total excess mortality from all causes or the excess bloodshed due to all respiratory causes [8, 24]. As influenza infections are known to occur meantime with other respiratory illnesses and may non be diagnosed as influenza, pneumonia, bronco-pneumonia, bronchitis, and lung congestion cases were also abstracted in add-on to influenza [25, 26]. Due to the high prevalence of tuberculosis in Arizona, tuberculosis deaths were excluded from the excess bloodshed, standardized mortality ratio, and reproduction number calculations based on respiratory causes. Information about age, gender, verbal date of expiry, and/or cause of expiry were not available for <1 % of all records.
Qualitative data
To provide anecdotal references near the form of the pandemic in Maricopa County during 1957–1958, we examined the most popular daily paper of the area, The Arizona Commonwealth, which was published in Phoenix, Arizona. From June 1957-March 1958, there were 65 articles referencing influenza, 12 of which included news of Maricopa County. These archival newspaper articles were manually retrieved from the Arizona State University microform library in Tempe, Arizona. This data was used to create a timeline of relevant events and non-pharmacological mitigation strategies employed in Arizona during the pandemic period.
Statistical methods
Population estimates
Although the United states Demography Agency provided detailed population data every decade, sufficient Maricopa County population data were not bachelor for 1954–1959 and 1961. As the Maricopa County population about doubled between 1950 and 1960, we estimated the population values for the intercensal years of 1954–1959 and 1961. To estimate the total Maricopa County population for each week from Jan 3, 1954 to December 3, 1961, a polynomial model was applied to county population data provided past the 1950 and 1960 United States Censuses as well every bit Valley National Depository financial institution annual January intercensal county estimates spanning from 1951 through 1959 and 1961 [18, 19, 27].
Using the total and age-specific canton population data from the 1950 and 1960 Usa Censuses, we calculated the proportion of each historic period-specific population to the total county population for 1950 and 1960 and used polynomial models to gauge the age-specific to total county population proportions for each week from January iii, 1954 to December 3, 1961. These estimated age-specific to total county population proportions for each week were then multiplied by the previously estimated total Maricopa County population for the same week to approximate the weekly historic period-specific population values from January iii, 1954 to December 3, 1961. The proportion and final weekly age-specific population estimation steps were repeated for each age category. These historic period-specific Maricopa County population estimates were used to summate age-specific mortality values. To represent the estimated total county population for each week, all the final age-specific estimations were summed for that week and these sums were used to calculate mortality values for all-ages.
Instead of directly estimating the weekly age-specific population values from the two data points of the 1950 and 1960 U.S. censuses, this process was chosen in order to account for the gradual change in historic period-specific proportions while including the additional data from the Valley National Banking company intercensal canton estimates to create a more representative model. Additionally, this method accounts for specific deviations betwixt age groups besides as for changes in the age construction of the population past including the historic period-specific populations of 1950 and 1960 in the models.
Bloodshed data
To represent the mortality rate linked to the 1957–1958 influenza pandemic in Maricopa Canton, we quantified the excess mortality per x,000 people for each historic period category and each expected pandemic wave. For each expected wave and age group, backlog bloodshed was divers as the number of deaths during the pandemic catamenia greater than the baseline mortality from a comparable time menstruum without epidemic influenza (Excess Mortality = bloodshed during epidemic catamenia- baseline mortality) [10]. Weekly bloodshed data for the pre-pandemic period of January iii, 1954-June 30, 1957 and a cyclical Serfling linear regression model, including temporal trends and harmonic terms for seasonality, were utilized to estimate the baseline bloodshed [28, 29]. Based on a time serial of monthly respiratory mortality rates of all-ages, 3 expected pandemic waves were chosen for backlog mortality analysis: Oct 1, 1957-March 31, 1958, October ane, 1958-June 30, 1959, and October i, 1959-June 30, 1960. The model used to judge baseline-mortality was expressed as: weekly death rates(t) = intercept + αi* t + αtwo(t/100)ii + α3(t/100)three + α4(t/100)4 + β1sin(2*π/52.17*t) + γ1cos(2*π/52.17*t) + βtwosin(4*π/52.17*t) + γ2cos(4*π/52.17*t) + β3sin(8*π/52.17*t) + γiiicos(8*π/52.17* t), where t represented the week number and α, β, and γ were coefficients to exist estimated from the information. In the above model, α represented the fourth dimension tendency and β and γ represented seasonal changes. The baseline-bloodshed model was adapted from Chowell et al. [28].
During each expected wave, pandemic periods were classified every bit weeks with respiratory or all-cause mortality above the 95 % upper conviction limit (UCL) of the baseline mortality. Weekly backlog mortality was equal to the number of deaths greater than the baseline model during these pandemic periods. To detect the absolute bloodshed burden of each expected pandemic wave in 1957–1960, the excess deaths greater than the baseline bloodshed were summed during each pandemic flow [two, 29]. Separate models with historic period-specific population values and historic period-specific weekly deaths were fit to each historic period category for both respiratory deaths and all-causes.
Additionally, we calculated the ratio of observed bloodshed during the pandemic periods to the expected baseline bloodshed of a menstruation lacking pandemic influenza, or the standardized bloodshed ratio (SMR) for pandemic-related death. To guess the mortality attributable to the influenza pandemic, we calculated mortality rate in excess of a seasonal model baseline. The expected baseline mortality for a period lacking pandemic flu was estimated using the cyclical Serfling linear regression model previously described also equally bloodshed data from the pre-pandemic period from January 3, 1954 to June 30, 1957. These mortality ratios have been standardized by the same age categories used for backlog bloodshed. Standardized mortality ratio is interpreted relative to i, with values greater than i representing an increased risk of expiry in individuals exposed to the H2N2 virus compared to individuals who were unexposed.
Reproduction numbers (transmission characteristics)
For each expected pandemic wave, we estimated the intrinsic transmission factor. At the showtime of an epidemic, the transmission gene of a pathogen is measured by the basic reproduction number (R0), the average number of secondary cases generated past a main case in a completely naive population [2, thirty, 31, 34]. Nevertheless, equally the outbreak continues, the population is no longer completely susceptible due to adaptive immunity [32]. In a partially immune population, the transmission potential during the initial epidemic menses is defined as the reproduction number (R). As at that place is slight or no background population immunity during the initial wave of a pandemic, R is expected to approximately equal R0 during the beginning of the first wave. However, based on the flavour that the new virus was introduced to local populations, the reproduction number may vary geographically and temporally [2].
A growth rate method was used to estimate the reproduction number. The growth rate (r) measures how quickly the number of cases increases through time and is estimated by assuming an exponential function to the initial increase in the weekly respiratory deaths. A straight line can be modeled to the data through taking the log of weekly deaths during the ascending phase, using the following regression: log(weekly cases(t)) =intercept +r ∗t, where t = a daily index and r = an estimated regression coefficient that represents the exponential growth rate.
The ascending phase was defined as the fourth dimension between the week the pandemic began, the first calendar week of the menstruation with continuously increasing deaths, and the calendar week the wave peaked. Based on the Susceptible-Exposed-Infectious-Recovered transmission model, the reproduction number was calculated by substituting r into the following equation: where =mean latent menstruum and = mean infectious period. In the previous equation for R, the latent and infectious periods are assumed to be exponentially distributed and the mean generation interval is found by .
Additionally, an upper bound estimate in the instance of a fixed generation interval (delta distribution) was obtained with the following equation: R =e r T C .
As the generation interval for influenza is uncertain, ii generation intervals were used. A short generation interval of 3 days, with a latency flow of 1.5 days and an infectious period of 1.5 days, was used. Additionally, a longer generation interval of four days, with a latency flow of 2 days and an infectious menstruum of ii days, was used. The generation interval measures the length of time between when symptoms develop in 2 consecutive cases and is made upwardly past the infectious period of the initial instance and the latency flow of the second case [2, 28, 33].
Results
Local newspapers, 1957–1958
The first article in The Arizona Commonwealth of an influenza outbreak in Arizona appeared on August 24, 1957 when about 75–100 prisoners at Arizona State Prison in Pinal County had influenza-like symptoms (see Fig.1) [35]. On September 19, 1957 another outbreak was reported from Fort Huachuca in Cochise County and all places of public gathering were closed due to 225 cases of influenza, unconfirmed every bit the H2N2 strain [36, 37]. After its introduction into Arizona, the influenza virus spread apace throughout the state. The kickoff confirmed instance of "Asian" influenza in Arizona, which involved a Phoenix resident, was reported on September 23, 1957 [14]. There had been fourteen,034 cases of influenza reported in Arizona from the beginning of the year to September 25, 1957, when the transmission of the virus reached epidemic levels, according to the state wellness commissioner [38]. In Maricopa Canton specifically, there had been 5112 cases of influenza during the twelvemonth by September 26, 1957 and flu cases continued to ascent rapidly [39].
Timeline of Events in Arizona. A summary of the major events documenting the severity and spread of flu and other respiratory illnesses in Arizona during the introduction of the H2N2 virus, based on articles in The Arizona Republic from June 1957-March 1958. For a more complete set of manufactures meet https://world wide web.dropbox.com/sh/irz1zzf8z613p8j/AACLkXzyXikWqskIssRv7aBha?dl=0
On December viii, 1957, the state wellness commissioner reported an increase in flu cases throughout the state, with Maricopa County being one of the about affected regions. In the week prior to his proclamation, there had been 2942 cases of influenza, representing nearly a quarter of the actual cases in the state [40]. As time progressed into early on 1958, there were fewer reports on influenza in Maricopa County and Arizona.
Backlog mortality and standardized mortality ratio attributable to influenza
Bloodshed from 1957–1961 was extremely balmy in Maricopa County, compared to previous influenza pandemics. The respiratory mortality weekly time series for all-ages in Maricopa Canton demonstrated evidence only of two balmy pandemic waves during the 1957–1960 pandemic time period: a 7 week period from January ten, 1960 until February 28, 1960 and a 3 week period from Apr 17, 1960 until May 8, 1960 (Fig.2). Based on all-causes, there were three short periods of backlog bloodshed for all-ages: a ane-week flow from November 9, 1958 until November 16, 1958, a 1-week period from April 19, 1959 until April 26, 1959, and ane-week period from May 1, 1960 until May 8, 1960 (Fig.3).
Age-specific respiratory mortality weekly time series. 2 Age-specific weekly time series of respiratory bloodshed per 10,000 population in Maricopa Canton, Arizona, 1954–1961. Areas outlined in gray represent the three expected pandemic waves: October one, 1957-March 31, 1958; October 1, 1958-June xxx, 1959; and October 1, 1959-June xxx, 1960. The baseline mortality (black) was estimated using a cyclical Serfling linear regression model. The baseline mortality'due south 95 % upper conviction limit (UCL) is likewise shown (ruddy). Mortality attributable to the 1957 influenza pandemic was defined as the mortality rates (blue) in excess of the baseline bloodshed, when the mortality rates exceeded the 95 % UCL of the baseline mortality during the expected pandemic waves
Historic period-specific all-cause mortality weekly time series. Historic period-specific weekly time series of all-cause mortality per 10,000 population in Maricopa County, Arizona, 1954–1961. Areas outlined in gray stand for the three expected pandemic waves: October 1, 1957-March 31, 1958; October 1, 1958-June 30, 1959; and October 1, 1959-June 30, 1960. The baseline mortality (blackness) was estimated using a cyclical Serfling linear regression model. The baseline mortality's 95 % upper confidence limit (UCL) is also shown (ruddy). Mortality attributable to the 1957 influenza pandemic was defined as the bloodshed rates (blue) in backlog of the baseline mortality, when the mortality rates exceeded the 95 % UCL of the baseline mortality during the expected pandemic waves
The absolute backlog-mortality rates per 10,000 population for each predicted wave were summed for respiratory illnesses (Table1) and all-causes (Tabular arrayii). In general, absolute excess mortality remained very low in those younger than 24 and increased with historic period in deaths due to all-causes, with some variation between waves. In absolute excess mortality due to respiratory causes, there was more variation with age. With the exception of respiratory causes during the 1958 wave, absolute excess-mortality for respiratory or all-causes peaked among the elderly (≥65 years).
Table i
Estimated historic period-specific absolute excess mortality rates and standardized bloodshed ratios for respiratory causes of death, Maricopa Cantona
| 1957 | 1958 | 1959 | ||||
|---|---|---|---|---|---|---|
| Age Grouping (yrs) | Backlog mortality rate/10,000 population | SMR | Excess mortality rate/10,000 population | SMR | Excess mortality rate/10,000 population | SMR |
| All ages | 0.00 | 1.17 | 0.00 | 1.01 | i.80 | i.31 |
| <5 | 0.00 | 0.95 | 0.00 | 0.85 | 0.75 | 1.04 |
| 5–xiv | 0.22 | 4.06 | 0.xvi | 1.37 | 0.38 | 3.28 |
| 15–24 | 0.19 | 1.16 | 0.lxx | ane.88 | 0.00 | 0.81 |
| 25–44 | 0.08 | ane.24 | 0.23 | 1.forty | 0.38 | 1.40 |
| 45–64 | 0.72 | 1.23 | one.01 | 1.02 | ii.48 | 1.32 |
| ≥65 | 2.52 | 1.eighteen | 0.00 | 0.99 | 16.59 | i.36 |
aAbsolute backlog bloodshed rates/10,000 population based a cyclical Serfling linear regression model and weekly respiratory mortality rates during the three expected pandemic waves: Oct i, 1957-March 31, 1958 (1957), October one, 1958-June 30, 1959 (1958), and October 1, 1959-June 30, 1960 (1959)
Table 2
Estimated historic period-specific accented backlog mortality rates and standardized mortality ratios for all-causes of death, Maricopa Cantona
| 1957 | 1958 | 1959 | ||||
|---|---|---|---|---|---|---|
| Age Grouping (yrs) | Excess mortality rate/10,000 population | SMR | Excess mortality rate/ten,000 population | SMR | Backlog mortality rate/10,000 population | SMR |
| All ages | 0.00 | 1.05 | 0.64 | one.03 | 0.31 | i.06 |
| <5 | 0.00 | 0.87 | 0.00 | 0.98 | 0.00 | one.01 |
| 5–fourteen | 0.00 | 0.90 | 0.00 | 0.85 | 0.48 | 1.25 |
| xv–24 | 0.00 | 0.91 | 0.00 | 0.85 | one.08 | one.24 |
| 25–44 | 0.53 | 1.08 | 0.77 | 1.15 | 1.06 | 1.eleven |
| 45–64 | 0.74 | 1.10 | i.41 | ane.02 | 0.73 | 1.03 |
| ≥65 | 1.85 | 1.09 | three.50 | ane.02 | one.73 | ane.02 |
aAbsolute backlog mortality rates/x,000 population based a cyclical Serfling linear regression model and weekly all-cause mortality rates during the three expected pandemic waves: October i, 1957-March 31, 1958 (1957), October one, 1958-June 30, 1959 (1958), and October 1, 1959-June 30, 1960 (1959)
The absolute excess-mortality rates per 10,000 population for each predicted moving ridge were compared for respiratory illness (Fig. four) and for all-causes (Fig. five).In a comparison of the three predicted waves, the greatest absolute backlog mortality rate based on respiratory illnesses was observed in those over 65 years of age during the 1959 predicted moving ridge. The 1959 predicted wave demonstrated relatively high absolute excess morality due to respiratory causes in older populations but low values in those younger than 44, with a slight superlative at those younger than v years.
Historic period-specific accented respiratory excess mortality rates/10,000 population. Age-specific absolute excess-bloodshed rates per 10,000 population during the iii expected pandemic waves (October 1, 1957-March 31, 1958; Oct 1, 1958-June 30, 1959; and October 1, 1959-June 30, 1960) of the 1957 pandemic in Maricopa County, Arizona based on deaths attributed to respiratory illnesses. Estimates were in excess of baseline mortality rates for a period with non-epidemic influenza based on a cyclical Serfling linear regression model and weekly respiratory mortality rates
Historic period-specific accented all-cause excess mortality rates/10,000 population. Age-specific accented excess-mortality rates per 10,000 population during 3 expected pandemic waves (October 1, 1957-March 31, 1958; October i, 1958-June 30, 1959; and October 1, 1959-June 30, 1960) of the 1957 pandemic in Maricopa County, Arizona based on deaths attributed to all-causes. Estimates were in excess of baseline mortality rates for a period with non-epidemic influenza based on a cyclical Serfling linear regression model and weekly all-cause mortality rates
For absolute backlog mortality based on all-causes, the highest value in a comparison of the iii predicted waves was observed during the 1958 wave in those ≥65 years. In all predicted waves, the ≥65 age group experienced the greatest absolute excess-mortality due to all-causes.
To better compare unlike historic period groups, which take different background risks of death, the run a risk for mortality rates relative to baseline-mortality rates were calculated for respiratory causes (Table1) and all-causes (Table2). While absolute excess-mortality was by and large greatest amid the elderly, the standardized bloodshed ratio was greatest in children (5–fourteen years) for respiratory causes. For children and young adolescents (5–xiv), bloodshed rates increased iv.06-fold above baseline-mortality rates for respiratory causes during the 1957 wave. For all-causes, the standardized mortality ratio was greatest in children (5–14) in the 1959 expected wave, when mortality rates increased ane.25-fold above baseline-mortality rates. For all-ages, in that location were ane.fourscore excess respiratory deaths during all three predicted waves.
Reproduction numbers (transmission characteristics)
Estimates for the reproduction number, based on growth in weekly respiratory death rates, for each predicted wave of the 1957 pandemic in Maricopa County are listed in Tableiii. The 1957 wave had the greatest value for R with 1.08, using a brusk generation interval of iii days, and i.x–1.11, using a longer generation interval of iv days.
Table 3
Hateful estimates of the reproduction number (R) and 95 % confidence levels due to respiratory causesa
| iii-day generation interval | iv-day generation interval | |||
|---|---|---|---|---|
| Wave | Exp. distribution | Delta distribution | Exp. distribution | Delta distribution |
| 1957 | 1.08 (0.99, 1.17) | i.08 (0.99, 1.18) | one.ten (0.99, 1.23) | 1.eleven (0.99, i.24) |
| 1958 | i.05 (1.00, 1.11) | 1.05 (ane.00, ane.eleven) | ane.07 (i.00, one.14) | 1.07 (1.00, 1.15) |
| 1959 | 1.05 (1.01, 1.08) | one.05 (one.01, one.08) | one.07 (1.02, 1.11) | ane.07 (one.02, ane.12) |
aValues were estimated from weekly data based on three expected pandemic waves: October 1, 1957-March 31, 1958 (1957), October 1, 1958-June xxx, 1959 (1958), and October one, 1959-June 30, 1960 (1959). A generation interval of 3 or 4 days was assumed, with an exponential (exp.) or fixed (delta) distribution
Give-and-take
Past analyzing primary data from archival death certificates from 1954 to 1961 and archival paper articles, we found that Maricopa County exhibited low bloodshed impact associated with the 1957 influenza pandemic, compared with other regions of the United states. In the United States, backlog mortality values for all-ages from pneumonia and flu deaths as well equally from all-cause deaths were greatest from Oct-Dec 1957, compared to January-March 1958 and Jan-March 1960 [xi]. From September 1957 to March 1958, the Usa had a 4.v (per x,000) absolute all-crusade excess mortality value for all ages and a ane.17 (per 10,000) absolute flu-pneumonia backlog mortality value for all ages [10]. However, in Maricopa County, the accented respiratory excess mortality for all-ages was greatest (one.8 per 10,000) during the 1959–1960 wave and excess bloodshed peaked in the starting time calendar week of May 1960. While some age groups did accept extremely mild backlog-mortality during Oct one, 1957-March 31, 1958 or during Oct one, 1958-June 30, 1959, there was little overall bear witness for herald waves in 1957 or 1958, based on respiratory deaths. This is consistent with the less pronounced mortality from January-March 1958 and the higher excess mortality from 1959 to 1960 in the Mount region compared to other regions of the U.Southward. [11]. Accented all-cause excess mortality (per x,000) in Maricopa County was greatest from Oct 1, 1958-June 30, 1959, for all-ages (0.64) and for the elderly (≥65) (3.50). Yet, absolute excess-mortality from all-causes was minimal throughout all predicted waves. Interestingly, there was likewise some excess-bloodshed from respiratory or all-causes during the calendar week of June two, 1957 or during June 29, 1958-July twenty, 1958 for some age groups, merely non overall. We cannot dominion out the potential contribution of high temperature in the region to excess bloodshed during these summer months. It has also been suggested that influenza epidemics may coincide with rainy reasons in the tropics due to indoor crowding [16]. However, influenza manual in Maricopa County seems to be more efficient in cold, dry out weather with low air pressure. Soebiyanto et al. also demonstrated that flu cases in Maricopa County do not seem to be associated with rainfall [41].
The virus seemed to accept been introduced in Maricopa County relatively late, betwixt August 23, 1957 and September 23rd, 1957 [fourteen, 35]. The U.S. had seen its first case by June and the commencement epidemic in the U.S. occurred in early on Baronial in the southeast of the U.S. [6, thirteen]. However, the first example of the H2N2 virus in Arizona was not confirmed until September 23, 1957 and transmission reached epidemic levels in Arizona on September 25, 1957 [fourteen, 38]. 1 of the major factors for the emerging community epidemics in the autumn of 1957 was the opening of schools around September [6]. Mortality began to rise during the 4th calendar week of October 1957, about 3 weeks later the rest of the U.S. [11]. Mortality in Maricopa County peaked in the tertiary week of November 1957, near two weeks after other regions of the U.S. [xi]. According to paper reports, influenza incidence in Maricopa County was nonetheless ascent rapidly on September 26, 1957 and seemed to continue to rise at to the lowest degree through November 1, 1957 [39, 42]. A rise in mortality can follow a ascent in acute respiratory illness incidence by equally much every bit 3–4 weeks [11]. This lag between morbidity and bloodshed may exist because the 1957 influenza virus generally afflicted high school historic period adolescents first, followed by elementary school students, and the adult population last. [13]. Incidence in the United States was especially high in those between v and nineteen and everyman in those 65 and older. However, bloodshed was highest in those 65 and older [13]. Our results ostend that age-patterns in Maricopa County were similar to those from the rest of the Us, with the excess-mortality full-bodied in the elderly (≥65). While incidence may accept been loftier in children and adolescents, this age group experienced minimal excess-mortality, avoiding the effects of an over-reactive allowed system and the over-production of cytokines theorized for the high mortality rates of immature adults reported during the 1918 pandemic [43]. Instead, younger individuals may accept transmitted the virus to the elderly after a couple of weeks of high incidence in schoolhouse-aged populations. While individuals >67 years of age may accept had antibodies for the 1957 H2N2 virus due to a mayhap related pandemic in 1889–90, individuals ≥65 years of age also had a high-risk of death from influenza in 1957 due to cardiovascular disease and bronco-pulmonary co-morbidities [eight, 44].
From October 1957-March 1958, excess deaths from all-causes in the United states were greatest in the elderly (≥65) and demonstrated a U-shaped age-pattern (high mortality in infants and elderly with depression mortality in immature adults). While all-crusade excess deaths were concentrated in those 65 and older, there were no all-cause excess deaths in infants (≤1 twelvemonth) and depression all-cause excess deaths in children (i–xiv years), avoiding the U-shaped historic period pattern in the United States from Jan-March 1960 [11]. With the exception of backlog-mortality rates from respiratory causes during October 1, 1958-June 30, 1959, backlog-expiry rates in Maricopa Canton were greatest in the elderly and had minimal values in younger age groups. While other periods demonstrated no backlog-mortality in young children (≤v), the 1959–1960 wave had a very slight summit in backlog-mortality for the historic period group. All the same, the backlog-bloodshed in those less than 5 years did not approach that of the elderly, as is common in a traditional U-shaped historic period-blueprint. Therefore, the historic period-blueprint did not truly resemble a U-shaped curve.
For both all-causes and respiratory illnesses, the standardized mortality ratios were minimal for near historic period groups throughout all three waves. Most likely due to crowding in schools, the standardized mortality ratio peaked (four.06) in young children and adolescents (5–14 years) from Oct 1, 1957-March 31, 1958, based on mortality rates of respiratory deaths. This is consistent with what was reported by Dauer: the epidemic in September 1957 began in high schools and colleges and moved into elementary schools and pre-school children. Yet, in the United states from October-December 1957, the standardized mortality ratio was highest (~2.25) in those thirty–39 years old, perhaps due to proximity in the workplace [10]. Additionally, it is of import to note that although the standardized bloodshed ratio was elevated for children and adolescents during the 1957 wave, the backlog-mortality rate was minimal for the same historic period group and time period. However, these results are not contradictory. While the baseline mortality was a fraction of the observed bloodshed during the 1957 wave, the difference between the values was negligible for young children and adolescents. This may be due to a relatively low baseline mortality in those aged 5–14, compared to other age groups. In contrast, the higher backlog mortality rate and the low SMR seen in those ≥65 during the 1959 moving ridge may be due to a higher baseline mortality for the elderly, when compared to other age-categories.
Although the respiratory excess-mortality rates during the 1957 and 1959 waves both disproportionally affected the elderly, there was a shift to greater excess mortality in the latter wave. A previous report showed that excess-mortality during the 1959 wave was full-bodied in the elderly and approached the excess-bloodshed rate of the 1957 moving ridge [xi]. While excess-bloodshed may have increased betwixt waves in Maricopa County, the possibility that the 1959 moving ridge could have been due to a different flu strain cannot exist ruled out. This written report however did not address evidence demonstrating that the 1959–1960 ascendant strain in Maricopa County was the 1957 pandemic strain.
To estimate the baseline mortality from a not-epidemic catamenia, this report utilized mortality information from Jan 3, 1954 to June 30, 1957. Baseline periods vary in length between studies and longer periods may exist used for country-broad analyses. Using a longer period to gauge baseline mortality may have increased the accuracy of the Serfling model. However, a three-year menses has been previously used to guess the epidemic threshold of smaller populations, such every bit cities or counties, in which there is reduced variation [2].
Our calculation of excess mortality is non exempted of limitations. In item, due to lack of laboratory confirmation, our excess mortality approach would not have been unable to distinguish elevation in mortality rates associated with other causes and coinciding with the pandemic period. Our approach for calculating excess mortality was relatively simple, due to lack of contemporaneous virological surveillance. Moreover, by grouping deaths into all-cause bloodshed and respiratory mortality categories, the study prioritized sensitivity over specificity. Because influenza deaths are oft attributed incorrectly, we believe that categorizing deaths into all-causes and respiratory causes provides conservative estimates of excess mortality.
Reproduction numbers were relatively similar betwixt waves, assuming mean generation intervals of three or 4 days that follow exponential or fixed distributions. In the Britain, R0 was estimated to be one.7–1.8 for an infectious menstruation of ii days and 1.5–1.half dozen if the infectious period was i.5 days [45]. Thus, the Maricopa County mean reproduction number of 1.08–1.11, using 3 or 4 day generation intervals and exponential or fixed distributions, was substantially lower than that observed in the UK. However, the reproduction number is preferably calculated from case incidence curves rather than fourth dimension series of deaths. Consequently, it is likely that our R0 estimates could exist slightly underestimated. Nevertheless, the lower reproduction number observed in Maricopa County in the 1957–1958 pandemic wave was most likely non due to the public health interventions put in place in the fall of 1957. While endmost schools can reduce the furnishings of an epidemic by 22 %, when the R0 is low (≤1.8) [45], the country health department seemed to implement few not-pharmacological mitigation strategies, and instead urged residents to receive an influenza vaccine and communicated the symptoms of Asian flu [46, 47]. While Valley of the Lord's day School airtight for about five days on September 30th, when absences reached 39 % of enrollment, most schools remained opened [48]. Absences reached 25 % of enrollment in Glendale schools, 20 % at St. Francis Xavier School, and 25 % at Tempe High School [48]. However, absences in Phoenix simple schools in the first calendar week of Oct were only 13 % of enrollment [49].
While some take theorized that the 1918 and 1957 differed in virulence, the differences in the rates of severe disease are likely due to medical and public health advances. In 1918–xix, almost all of the well-observed flu deaths were due to bacterial infections in the lungs [50]. Similarly, in 1957, deaths were often associated with bacterial pneumonia and staphylococcal infections [51]. However, unlike the 1918 pandemic, secondary bacterial infections were partially controlled through antimicrobials in 1957 [7]. The bacterial infections that did result in death were generally multidrug resistant [52]. 1957 was the first time a pandemic virus was available for laboratory analysis and the first time that an influenza vaccine became available [7, 50, 52]. Although 22,017 vaccine doses were reportedly allocated to Arizona, newspaper reports suggest that many of these doses had not been received by November 1957 [38, 53] casting doubtfulness on the explanation that depression bloodshed rates in Maricopa County might be explained by vaccine administration.
Climate and its effects on virus survival and manual may be a possible explanation for the lower bloodshed rates and reproduction numbers observed in Maricopa County during the expected waves. Influenza virus survival is optimal at low temperatures, low sunlight, and low accented humidity [16]. However, while humidity was by and large depression in Maricopa County, temperature and sunlight during the wintertime were not low, compared with other regions of the U.S. These environmental conditions may have contributed to the decreased reproduction number and mortality rates, as it would have been more difficult for the virus to survive manual between hosts.
Conclusions
By using master data from archival death certificates from 1954 to 1961 to quantify the age, seasonal, and transmissibility patterns of the second influenza pandemic of the 20th century, this study confirmed that Maricopa County largely avoided the furnishings of the 1957 pandemic. Compared to other regions of the Usa, Maricopa Canton had few excess deaths due to the 1957 influenza pandemic. Although results varied between age groups, the 1957 pandemic in Maricopa County was characterized past a mild wave from October i, 1959 to June thirty, 1960, when there were 16.59 absolute excess-deaths due to respiratory causes per 10,000 population in the elderly (≥65 years), the age group nearly affected. However, the standardized bloodshed ratio peaked (4.06) in children and young adolescents (v–14 years) from October 1, 1957-March 31, 1958, based on mortality rates of respiratory deaths. Transmissibility was greatest during the same 1957–1958 catamenia, when the mean reproduction number was a low one.08–1.11, using 3 or four-day generation intervals and exponential or fixed distributions.
Through analyzing archived paper articles, the low mortality and transmissibility rates recorded in Maricopa County were about probable not due to public health interventions or vaccine distribution. While there is much unknown nigh climate and virus survival, the environmental conditions in Maricopa Canton may have prevented loftier manual and excess-mortality rates. By analyzing historical data of different regions, researchers can better understand how mortality and transmission rates are related to different environmental conditions and public health interventions, providing important lessons to optimize electric current state-level preparedness and control plans.
Abbreviations
R, Reproduction number; R0, Bones reproduction number; SMR, Standardized bloodshed ratio; UCL, Upper confidence limit; r, Growth rate
Acknowledgements
We would like to thank the undergraduate students who assisted in collecting the raw data. April Cobos would like to thank Melinda Jenner for advice on mathematical modeling tools. This piece of work was partially supported past the Multinational Influenza Seasonal Mortality Study (MISMS), an on-going international collaborative try to sympathise flu epidemiological and evolutionary patterns, led by the Fogarty International Heart, National Institutes of Wellness (http://www.origem.info/misms/alphabetize.php).
Availability of data and materials
The dataset supporting the conclusions of this article is available in the Arizona Genealogy Nascence and Death Document repository, http://genealogy.az.gov.
Authors' contributions
GC contributed to the formulation of this report; GC, CV, MJ, AJC contributed to the study design; GC and CV designed and developed the data collection tools; GC, CGN, and AJC assisted in acquiring the data and in the literature review; GC and AJC analyzed and interpreted the data. GC, MJ, and AJC drafted the manuscript. All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
Non applicable.
Ideals approval and consent to participate
Not applicable. Data are publicly bachelor online from the Arizona Role of Vital Records at http://genealogy.az.gov.
Contributor Information
April J. Cobos, Email: ude.us@sobocja.
Clinton G. Nelson, Email: ude.united states of america@noslengc.
Megan Jehn, Electronic mail: ude.usa@nhej.nagem.
Cécile Viboud, E-mail: vog.hin.liam@cduobiv.
Gerardo Chowell, Email: ude.usg@llewohcg.
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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4982429/
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