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Gender differences in measles incidence rates in a multi-year, pooled analysis, based on national data from seven high income countries

BMC Infectious Diseases volume 22, Article number: 358 (2022) Cite this article

Abstract

Background

Gender differences in a number of infectious diseases have been reported. The evidence for gender differences in clinical measles incidence rates has been variable and poorly documented over age groups, countries and time periods.

Methods

We obtained data on cases of measles by sex and age group over a period of 11–27 years from seven countries. Male to female incidence rate ratios (IRR) were computed for each year, by country and age group. For each age group, we used meta-analytic methods to combine the IRRs. Meta-regression was conducted to the estimate the effects of age, country, and time period on the IRR.

Results

In the age groups < 1, 1–4, 5–9, 10–14, 15–44, and 45–64 the pooled IRRs (with 95% CI) were 1.07 (1.02–1.11), 1.10 (1.07–1.14), 1.03 (1.00–1.05), 1.05 (0.99–1.11), 1.08 (0.95–1.23), and 0.82 (0.74–0.92) respectively. The excess incidence rates (IR) from measles in males up to age 45 are remarkably consistent across countries and time-periods. In the age group 45–64, there is an excess incidence in women.

Conclusions

The consistency of the excess incidence rates in young males suggest that the sex differences are more likely due to physiological and biological differences and not behavioral factors. At older ages, differential exposure can play a part. These findings can provide further keys to the understanding of mechanisms of infection and tailoring vaccination schedules.

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Introduction

Prior to immunization, measles was one of the commonest infectious diseases, affecting most children at an early age [1]. Despite the availability of an effective vaccine, achieving the goal of eradication remains elusive. Large epidemics continue to occur [2] and measles remains a major cause of childhood mortality, accounting for thousands of deaths annually [3]. The response to infection with measles is complex and not completely understood [4]. The virus replicates freely prior to the appearance of symptoms and clearance of viral RNA from blood and tissues takes some time after the rash disappears accompanied by a period of immunosuppression [4]. Following resolution of the infection, neutralizing antibodies persist and there is usually life-long immunity [4]. Based on serosurveys, the subclinical incidence of measles in very young children appears slightly higher than the incidence of clinically overt disease [5, 6]. A better understanding of the factors associated with developing clinical disease could contribute to determining optimal vaccine doses and schedules [7,8,9].

The reports on gender differences in clinical measles incidence rates have produced variable findings and there is poor documentation of such differences over age groups, countries and time periods [10,11,12,13,14]. The role of gender-related factors in measles morbidity could contribute to a better understanding of the mechanism of infection.

The main objective of the study was to use meta-analytic procedures to combine data from various countries at different times for different age groups, to obtain more stable estimates of the gender differences in measles incidence rates.

Methods

Source of data

National surveillance data on reported cases of measles, by age, sex and year, were obtained from relevant government institutions for seven countries from four continents: Europe (England, Germany, and Spain), Australasia (Australia and New Zealand), North America (Canada) and Asia (Israel). For Australia, for years 2001–2016, from the National Notifiable Diseases Surveillance System (NNDSS) [15], for Canada for the years 1991–2015, from the Public Health Agency of Canada (PHAC) [16], for England, for the years 1990–2016 directly from Public Health England (PHE), for Germany for the years 2001–2016, from the German Federal Health Monitoring System [17], for Israel from the Department of Epidemiology in the Ministry of Health for years 1991–2016, for New Zealand, for years 1997–2015 from the Institute of Environmental Science and Research (ESR) [18], and for Spain from the Spanish Epidemiological Surveillance for years 2005–2015 [19]. Information about the population size by age, sex and year was obtained for Australia from ABS.Stat [20] (Australia’s Bureau of statistics), for Canada from Statistics [21], Canada, CANSIM database, for England, from the Population Estimates Unit, Population Statistics Division, Office for National Statistics [22], for Germany from the German Federal Health Monitoring System [23], for Israel from the Central Bureau of Statistics [24], for New Zealand from Statistics New Zealand [25] and for Spain from the Department of Economic and Social Affairs, Population Division [26].

Statistical analyses

Measles incidence rates (IR) per 100,000 were calculated by sex, age group, for each country and calendar year using the number of reported cases divided by the respective population size and multiplied by 100,000. The age groups considered were < 1 year (infants), 1–4 (early childhood), 5–9 (late childhood), 10–14 (puberty), 15–39/44 (young adulthood) and 40–59 or 45–64 (middle adulthood). Surveillance system in Canada and New Zealand, used similar age-groups except for the following: 15–39 and 40–59. For Australia data for infants and 1–4 aged children disaggregated by sex are missing. The male to female incidence rate ratio (IRR) was calculated by dividing the incidence rate in males by that of females, by age group, country and time period.

Meta-analytic methods

As in previous studies of gender differences in infectious diseases [27,28,29,30], we used meta-analytic methods to establish the magnitude and consistency of the gender differences in the incidence of measles (disaggregated by age group, across different countries and a number of years). Meta-analysis is a statistical technique for summarizing the data from several sources into a weighted average. This method was used to generate single, quantitative estimates of the gender differences in the incidence of measles for each age group, combining data from a number of countries and time periods. The method provides improved power for determining more stable estimates of the outcome measure. The outcome measure in this study was the male to female IRR. For each age group, the IRRs for each country were pooled and then the pooled IRRs for each country were combined. Forest plots with the pooled IRRs, for the countries and years of reporting, were prepared separately for the six age groups. Heterogeneity of the IRRs was evaluated using the Q statistic and I2 was calculated as an estimate of the percentage of between-study variance. If the p-value for the Q statistic was < 0.05, or I2 was higher than 50%, the random effects models was used. Otherwise, the fixed effects model was considered, although due to the low power of the Q statistic, the more conservative random effects model was usually preferred. In order to explore the contribution of other variables as countries and the reported years, meta-regression analyses were performed. Leave-one-out sensitivity analysis was performed to estimate the effect of variables as different countries and years on the male to female incidence risk ratio. The meta-analyses and meta-regressions were carried out using STATA software version 12.1 (Stata Corp., College Station, TX).

Results

Descriptive statistics

The data on the measles incidence rates per 100,000 populations, by countries, sex and age groups are presented in Table 1. There were significant differences in the absolute incidence rates in in England and New Zealand, where the rates were high.

Table 1 Details of the countries included in the meta-analysis, by sex and age group—descriptive data
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Meta-analytic analyses

The forest plots for the pooled estimates using meta-analytic methods are shown by age group in Figs. 1, 2, 3, 4, 5, 6. The forest plot for infants is shown in Fig. 1.

Fig. 1
figure 1

Forest plot of the male to female measles IRRs for different years in Canada, England, Germany, Israel, New Zealand, and Spain in infants (< 1 years)

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Fig. 2
figure 2

Forest plot of the male to female measles IRRs for different years in Canada, England, Germany, Israel, New Zealand, and Spain for age 1–4 years

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Fig. 3
figure 3

Forest plot of the male to female measles IRRs for different years in Australia, Canada, England, Germany, Israel, New Zealand, and Spain for age 5–9 years

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Fig. 4
figure 4

Forest plot of the male to female measles IRRs for different years in Australia, Canada, England, Germany, Israel, New Zealand, and Spain for age 10–14 years

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Fig. 5
figure 5

Forest plot of the male to female measles IRRs for different years in Australia, Canada, England, Germany, Israel, New Zealand, and Spain for age 15–44 (or 15–39) years

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Fig. 6
figure 6

Forest plot of the male to female measles IRRs for different years in Australia, Canada, England, Germany, Israel, New Zealand, and Spain for age 45–64 (or 40–59) years

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There was an excess in incidence rates among males, with a pooled male to female IRR = 1.07, 95% CI 1.02–1.11, which varied between 1.02 in Canada and Germany to 1.40 in Israel.

The forest plot for the age 1–4 is shown in Fig. 2.

There was an excess in incidence rates for males with a pooled IRR = 1.10 and 95% CI 1.07–1.14, and ranged between 1.02 in Canada and 1.15 in Israel.

The forest plot for age 5–9 is given in Fig. 3.

There was an excess in incidence rates in males compared with females, with a pooled IRR = 1.03 and 95% CI 1.00–1.05. Subtotal IRR's varied between 0.85 in Spain to 1.15 in Israel.

The forest plot for age 10–14 is given in Fig. 4.

In the age group 10–14, there was an excess in incidence rates among males, with a pooled IRR = 1.05 and 95% CI 0.99–1.11. The IRR’s varied from 0.91 in Spain to 1.32 in New Zealand.

The forest plot for age 15–44 is given in Fig. 5.

For age 15–44, there was an excess in incidence rates in males with a pooled IRR = 1.08 and 95% CI 0.95–1.23. The IRR’s varied from 0.99 in Germany to 1.18 in Australia.

The forest plot for age 45–64 is given in Fig. 6.

For age 45–64 or 40–59, there was an excess in incidence rates in females with a pooled male to female IRR = 0.82 and 95% CI 0.74–0.92. The IRR’s varied from 0.76 in England to 1.28 in New Zealand. The numbers in the age group 65+ were too small for meaningful estimates.

A meta-regression analysis showed that most of the variance in the IRRs was contributed by the age groups, with some differences between countries and time periods. To evaluate the effect of individual countries on the male to female incidence ratios, we performed leave-one-out sensitivity analysis and recomputed the pooled IRRs (presented in Tables 2 and 3).

Table 2 Sensitivity analysis for countries, by age group
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Table 3 Sensitivity analysis for time periods, by age group
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After omitting each country (one country at a time), the pooled IRR’s were very similar. After omitting a group of years at a time, the pooled incidence RR’s still remained largely unchanged. Thus, no single country or group of years substantially affected the pooled IRRs. This confirms that the results are stable and robust. The changes in effect size are likely due to the relatively small numbers in the sub-groups. Sensitivity analysis by age group and country and by clusters of years were performed. No single country, including England or group of years affected the pooled IRRs.

Discussion

Based on meta-analytic analyses of national data from seven countries, over a period of 11–27 years, we found that the incidence rates of clinical measles were 7%, 10%, 3% and 5% significantly higher in males in infancy, ages 1–4, 5–9 and 10–14, respectively. In adults, the picture was less clear. In the age group 15–44, it was 8% higher in males, but with a wide confidence interval and not statistically significant. At age 44–64, the incidence rates were 18% lower in males. While the sex differences observed are not great, it has been shown that in infectious diseases where the clinical to subclinical ratio is relatively high, the observed gender differences tend to be lower in magnitude [31]. The variation in the absolute incidence rates can be explained, at least in part, by the occurrence of local outbreaks. For example during 1 year period, from 2012 to 2013, there were a series of outbreaks in England [10, 11]. New Zealand has suffered outbreaks due to measles importation [12].

Although a male predominance of measles incidence rates has been reported [32], to the best of our knowledge, there are no reports that combine data from different countries and time periods for different age groups. This study has several strengths. The study is based on national, notifiable diseases surveillance data with large total populations and numbers of cases. There should be minimal selection bias since we used national data for long periods for each country. A possible limitation is that there are likely to be differences between countries in diagnosis and reporting of measles. However, we do not believe that diagnosis or reporting differs between males and females, since the countries in this study do not have a culture of giving differential treatment according to sex. However, there could be differences between sexes in the use of health services. Since there is evidence that females tend to use health services more than males [33], the excess rates observed in males may underestimate of the true excess in the incidence rates in males. Differences in vaccination rates and national vaccination policies between countries should not affect sex-related differences in measles incidence. This pooled data analysis from seven countries does not include countries from Africa and Asia and thus, the findings may be generalizable only to high-income countries.

In this study we pooled age disaggregated data from seven countries, over a number of time-periods. As in previous studies of infectious diseases such as viral meningitis, shigellosis and campylobacteriosis, we used meta-analytic methods to pool the male to female IRRs over countries and time periods for separate age groups [27, 28, 30]. As in the current study, we found an excess in incidence rates in males at young ages [27, 28]. Pertussis is a notable exception, where females have been found to consistently have higher incidence rates at all ages [29].

It is of interest to note that sex differences in measles mortality rates have been reported. In one multi-national study, mortality from measles was examined in the WHO reports on causes of death in different countries over many years since 1950 [34]. The pooled results showed excess female mortality under the age of 50. However, in other studies, case-fatality rates were slightly higher for males of at ages [35, 36]. An interesting phenomenon is the excess mortality in females following the use of high-titer measles containing vaccines [37, 38]. Atabani et al. [39] suggested that this may be related to sex differences in antibody dependent cellular cytotoxicity, which they found to be lower in females following measles vaccination.

The exact mechanisms underlying the excess measles incidence rates in young males found in the current study are not clear and are likely to be multi-factorial. This study cannot address the mechanisms. However, it is possible to speculate on some possibilities. These include exposure differences, response to vaccines, genetic and hormonal factors. In infants and early childhood, it is unlikely that the sex differences in incidence rates are due to differences in exposure. At older ages, since females are generally over-represented as caregivers for sick children in healthcare or day-care facilites, one might expect higher incidence rates in the older age groups. This was not observed in the current study, except in the age group 45–64. Prior to the introduction of immunization in the late 1950’s, almost all children acquired measles, so measles in adults was uncommon. Measles in adults who have been immunized may be due to waning of immunity over time. While the measles vaccine is highly effective in preventing disease, gender differences have been found in response to measles vaccines. A study of children and adults in Spain found that females develop significantly higher measles IgG titers following vaccination in compare to age-matched males [40]. There is evidence of a weaker antibody response to measles vaccine in boys [41] and a higher humoral antibody response to live measles vaccine in females has been observed in young adults [42]. There also appears to be less waning in immunity to measles vaccine in females [43]. Thus, even after immunization, males may be more susceptible to measles than females.

Sex differences in measles incidence rates may be related to the imbalance in the expression of genes encoded on the X and Y-chromosomes of a host. The phenomenon of X chromosome inheritance and expression is a cause of immune disadvantage of males and the enhanced survival of females following immunological challenges [44]. The possible role of sex hormones remains largely unknown. Changes in male-to-female morbidity ratios with age may reflect differences between the sexes in immune and endocrine systems [45].

Estrogen may modulate cytokine production in vivo and contribute to sex-related differences in immune responses [46, 47]. Both, CD8+ and CD4+ T cells, which play significant roles during the rash phase of measles, express estrogen receptors (ERa and ERb) and are estrogen sensitive [48]. The surge in sex hormone levels in infancy that mimics sex steroid levels at puberty (‘minipuberty’) could affect immune cells differently in boys and girls and influence maturation of the immune system [49]. This transient rise in sex steroid levels may also impact on immune cells differently between boys and girls at later ages [50] and could play a role in the observed excess in incidence rates in males.

Conclusions

This study provides stable estimates of the magnitude of the excess male incidence rates in measles in most age groups, particularly in infants and children. Despite the generally high clinical to sub-clinical ratio, which may mask subtle sex differences in the incidence of clinical disease, the excess in young males is remarkably stable over a number of countries and for a period of around 20 years. A better understanding of the gender differences in disease incidence can help to elucidate genetic and hormonal determinants of measles infection and should be taken into account in the tailoring of vaccine doses and schedules.

Availability of data and materials

All data are available from the original sources or from the authors. The datasets analyzed during the current study are available from the corresponding author on reasonable request. For all countries, except Israel and England, public access to the databases is open and links are part of the references list. We received administrative permission from the official representative of Israeli Ministry of Health and Public Health England (PHE) to use the data for publication.

References

  1. Plans-Rubió P. Are the objectives proposed by the WHO for routine measles vaccination coverage and population measles immunity sufficient to achieve measles elimination from Europe? Vaccines (Basel). 2020;8:218. https://doi.org/10.3390/vaccines8020218.

    Article  Google Scholar 

  2. Ilyas M, Afzal S, Ahmad J, et al. The resurgence of measles infection and its associated complications in early childhood at a tertiary care hospital in Peshawar, Pakistan. Pol J Microbiol. 2020;69:1–8. https://doi.org/10.33073/pjm-2020-020.

    Article  PubMed  Google Scholar 

  3. Bentley J, Rouse J, Pinfield J. Measles: pathology, management and public health issues. Nurs Stand. 2014;28:51–8. https://doi.org/10.7748/ns.28.38.51.e8765.

    Article  PubMed  Google Scholar 

  4. Griffin DE. The immune response in measles: virus control, clearance and protective immunity. Viruses. 2016;8:282. https://doi.org/10.3390/v8100282.

    Article  CAS  PubMed Central  Google Scholar 

  5. Gendrel D, Chemillier-Truong M, Rodrique D, et al. Underestimation of the incidence of measles in a population of French children. Eur J Clin Microbiol Infect Dis. 1992;11:1156–7. https://doi.org/10.1007/BF01961134.

    Article  CAS  PubMed  Google Scholar 

  6. Martins C, Bale C, Garly ML, et al. Girls may have lower levels of maternal measles antibodies and higher risk of subclinical measles infection before the age of measles vaccination. Vaccine. 2009;27:5220–5. https://doi.org/10.1016/j.vaccine.2009.06.076.

    Article  PubMed  Google Scholar 

  7. Orenstein WA. The role of measles elimination in development of a national immunization program. Pediatr Infect Dis J. 2006;25:1093–101. https://doi.org/10.1097/01.inf.0000246840.13477.28.

    Article  PubMed  Google Scholar 

  8. World Health Organization. Global measles and rubella strategic plan: 2012–2020. Geneva: WHO Press, World Health Organization; 2012.

    Google Scholar 

  9. Montalti M, Kawalec A, Leoni E, Dallolio L. Measles immunization policies and vaccination coverage in EU/EEA countries over the last decade. Vaccines (Basel). 2020;8:86. https://doi.org/10.3390/vaccines8010086.

    Article  Google Scholar 

  10. Pegorie M, Shankar K, Welfare WS, et al. Measles outbreak in Greater Manchester, England, October 2012 to September 2013: epidemiology and control. Euro Surveill. 2014;19:20982. https://doi.org/10.2807/1560-7917.es2014.19.49.20982.

    Article  PubMed  Google Scholar 

  11. Vivancos R, Keenan A, Farmer S, et al. An ongoing large outbreak of measles in Merseyside, England, January to June 2012. Euro Surveill. 2012;17:20226. https://doi.org/10.2807/ese.17.31.20234-en.

    Article  PubMed  Google Scholar 

  12. Hayman DTS, Marshall JC, French NP, et al. Global importation and population risk factors for measles in New Zealand: a case study for highly immunized populations. Epidemiol Infect. 2017;145:1875–85. https://doi.org/10.1017/S0950268817000723.

    Article  CAS  PubMed  Google Scholar 

  13. Takla A, Wichmann O, Rieck T, et al. Measles incidence and reporting trends in Germany, 2007–2011. Bull World Health Organ. 2014;92:742–9. https://doi.org/10.2471/BLT.13.135145.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Richard JL, Vidondo B, Mäusezahl M. A 5-year comparison of performance of sentinel and mandatory notification surveillance systems for measles in Switzerland. Eur J Epidemiol. 2008;23:55–65. https://doi.org/10.1007/s10654-007-9187-1.

    Article  PubMed  Google Scholar 

  15. National Notifiable Diseases Surveillance System (NNDSS), Department of Health. http://www9.health.gov.au/cda/source/cda-index.cfm. Accessed 1 Apr 2018.

  16. Public Health Agency of Canada. https://www.canada.ca/en/public-health.html. Accessed 1 June 2018.

  17. German Federal Health Monitoring System. http://www.gbe-bund.de/gbe10/pkg_isgbe5.prc_isgbe?p_uid=gast&p_aid=0&p_sprache=D. Accessed 1 Feb 2018.

  18. Environmental Science and Research (ESR) for the Ministry of Health. https://surv.esr.cri.nz/surveillance/annual_surveillance.php. Accessed 30 Mar 2018.

  19. Instituto de Salud Carlos III (Informes anuales RENAVE). https://www.isciii.es/QueHacemos/Servicios/VigilanciaSaludPublicaRENAVE/EnfermedadesTransmisibles/Paginas/Informes-anuales-RENAVE.aspx. Some of the data can be obtained by searching the web. Keyword searched: RESULTADOS DE LA VIGILANCIA EPIDEMIOLÓGICA DE LAS ENFERMEDADES TRANSMISIBLES. INFORME ANNUAL Accessed 1 Mar 2018.

  20. ABS.Stat (Australian Bureau of Statistics). http://stat.data.abs.gov.au/Index.aspx?DatasetCode=ABS_ERP_ASGS2016. Accessed 15 May 2018.

  21. Statistics, Canada, CANSIM database. https://www150.statcan.gc.ca/t1/tbl1/en/cv.action?pid=1710010201. Accessed 1 June 2018.

  22. Population Estimates Unit, Population Statistics Division, Office for National Statistics. Available at: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/populationestimatesforukenglandandwalesscotlandandnorthernireland. Accessed 15 Mar 2018.

  23. German Federal Health Monitoring System. http://www.gbe-bund.de/gbe10/abrechnung.prc_abr_test_logon?p_uid=gast&p_aid=46300054&p_knoten=VR&p_sprache=E&p_suchstring=population. Accessed 1 Feb 2018.

  24. Central Bureau of Statistics. http://www.cbs.gov.il/reader/shnatonhnew_site.htm?sss=%E4%EE%F9%EA&shnaton_scan=45. Accessed 1 Mar 2018.

  25. Stats NZ. Infoshare. http://archive.stats.govt.nz/infoshare/SelectVariables.aspx?pxID=b854d8a2-3fdf-402c-af69-604112e80baa. Accessed 15 May 2018.

  26. Demographic Statistics Database (United Nations Statistics: Division). http://data.un.org/Data.aspx?d=POP&f=tableCode%3A22. Accessed 1 Apr 2018.

  27. Peer V, Schwartz N, Green MS. Consistent, excess viral meningitis incidence rates in young males: a multi-country, multi-year, meta-analysis of national data. The importance of sex as a biological variable. EClinicalMedicine. 2019;15:62–71. https://doi.org/10.1016/j.eclinm.2019.08.006.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Peer V, Schwartz N, Green MS. Sex differences in shigellosis incidence rates: analysis of national data from nine countries using meta-analytic method. Eur J Public Health. 2020. https://doi.org/10.1093/eurpub/ckaa087.

    Article  PubMed  Google Scholar 

  29. Peer V, Schwartz N, Green MS. A multi-country, multi-year, meta-analytic evaluation of the sex differences in age-specific pertussis incidence rates .PLoS ONE. 2020;15:e0231570. https://doi.org/10.1371/journal.pone.0231570.

  30. Green MS, Schwartz N, Peer V. Sex differences in campylobacteriosis incidence rates at different ages—a seven country, multi-year, meta-analysis. A potential mechanism for the infection. BMC Infect Dis. 2020;20:625. https://doi.org/10.1186/s12879-020-05351-6.

  31. Green MS. The male predominance in the incidence of infectious diseases in children: a postulated explanation for disparities in the literature. Int J Epidemiol. 1992;21:381–6. https://doi.org/10.1093/ije/21.2.381.

    Article  CAS  PubMed  Google Scholar 

  32. Wang X, Boulton ML, Montgomery JP, et al. The epidemiology of measles in Tianjin, China, 2005–2014. Vaccine. 2015;33:6186–91. https://doi.org/10.1016/j.vaccine.2015.10.008.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Bertakis KD, Azari R, Helms LJ, et al. Gender differences in the utilization of health care services. J Fam Pract. 2000;49:147–52.

    CAS  PubMed  Google Scholar 

  34. Garenne M. Sex differences in measles mortality: a world review. Int J Epidemiol. 1994;23:632–42. https://doi.org/10.1093/ije/23.3.632.

    Article  CAS  PubMed  Google Scholar 

  35. Nandy R, Handzel T, Zaneidou M, et al. Case-fatality rate during a measles outbreak in eastern Niger in 2003. Clin Infect Dis. 2006;42:322–8. https://doi.org/10.1086/499240.

    Article  PubMed  Google Scholar 

  36. Murhekar MV, Ahmad M, Shukla H, et al. Measles case fatality rate in Bihar, India, 2011–12. PLoS ONE. 2014;9: e96668. https://doi.org/10.1371/journal.pone.0096668.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Aaby P, Samb B, Simondon F, et al. Divergent mortality for male and female recipients of low-titer and high-titer measles vaccines in rural Senegal. Am J Epidemiol. 1993;138:746–55. https://doi.org/10.1093/oxfordjournals.aje.a116912.

    Article  CAS  PubMed  Google Scholar 

  38. Aaby P, Samb B, Simondon F, et al. Sex-specific differences in mortality after high-titre measles immunization in rural Senegal. Bull World Health Organ. 1994;72:761–70.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Atabani S, Landucci G, Steward MW, Whittle H, Tilles JG, Forthal DN. Sex-associated differences in the antibody-dependent cellular cytotoxicity antibody response to measles vaccines. Clin Diagn Lab Immunol. 2000;7:111–3. https://doi.org/10.1128/CDLI.7.1.111-113.2000.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Dominguez A, Plans P, Costa J, et al. Seroprevalence of measles, rubella, and mumps antibodies in Catalonia, Spain: results of a cross-sectional study. Eur J Clin Microbiol Infect Dis. 2006;25:310–7. https://doi.org/10.1007/s10096-006-0133-z.

    Article  CAS  PubMed  Google Scholar 

  41. Kontio M, Palmu AA, Syrjänen RK, et al. Similar antibody levels in 3-year-old children vaccinated against measles, mumps, and rubella at the age of 12 months or 18 months. J Infect Dis. 2016;213:2005–13. https://doi.org/10.1093/infdis/jiw058.

    Article  CAS  PubMed  Google Scholar 

  42. Green MS, Shohat T, Lerman Y, et al. Sex differences in the humoral antibody response to live measles vaccine in young adults. Int J Epidemiol. 1994;23:1078–81. https://doi.org/10.1093/ije/23.5.1078.

    Article  CAS  PubMed  Google Scholar 

  43. Bolotin S, Severini A, Hatchette T, et al. Assessment of population immunity to measles in Ontario, Canada: a Canadian Immunization Research Network (CIRN) study. Hum Vaccin Immunother. 2019;15:2856–64. https://doi.org/10.1080/21645515.2019.1619402.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Schurz H, Salie M, Tromp G, et al. The X chromosome and sex-specific effects in infectious disease susceptibility. Hum Genomics. 2019;13:2. https://doi.org/10.1186/s40246-018-0185-z.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Eshima N, Tokumaru O, Hara S, et al. Age-specific sex-related differences in infections: a statistical analysis of national surveillance data in Japan. PLoS ONE. 2012;7(7):e42261. https://doi.org/10.1371/journal.pone.0042261.

  46. Verthelyi D, Klinman DM. Sex hormone levels correlate with the activity of cytokine-secreting cells in vivo. Immunology. 2000;100:384–90. https://doi.org/10.1046/j.1365-2567.2000.00047.x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Bengtsson AK, Ryan EJ, Giordano D, Magaletti DM, Clark EA. 17beta-estradiol (E2) modulates cytokine and chemokine expression in human monocyte-derived dendritic cells. Blood. 2004;104:1404–10. https://doi.org/10.1182/blood-2003-10-3380.

  48. Adori M, Kiss E, Barad Z, et al. Estrogen augments the T cell-dependent but not the T-independent immune response. Cell Mol Life Sci. 2010;67:1661–74. https://doi.org/10.1007/s00018-010-0270-5.

    Article  CAS  PubMed  Google Scholar 

  49. Moreira-Filho CA, Bando SY, Bertonha FB, et al. Minipuberty and sexual dimorphism in the infant human thymus. Sci Rep. 2018;8:13169. https://doi.org/10.1038/s41598-018-31583-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Courant F, Aksglaede L, Antignac JP, et al. Assessment of circulating sex steroid levels in prepubertal and pubertal boys and girls by a novel ultrasensitive gas chromatography–tandem mass spectrometry method. J Clin Endocrinol Metab. 2010;95:82–92. https://doi.org/10.1210/jc.2009-1140.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We express our appreciation to the official institutions of each of the seven countries (Australia, Canada, England, Germany, Israel, New Zealand, and Spain) that published or provided data on the incidence of measles and thus allowed the study to be carried out.

Funding

No funding sources were used for the study.

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Authors and Affiliations

  1. School of Public Health, University of Haifa, Abba Khoushy 199, Mount Carmel, 3498838, Haifa, Israel

    Manfred S. Green, Naama Schwartz & Victoria Peer

Authors
  1. Manfred S. Green
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  2. Naama Schwartz
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  3. Victoria Peer
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Contributions

MSG designed and supervised the study and participated in the analysis and interpretation of the data and in writing the manuscript. NS assisted in the data analysis and contributed important input in the review of the manuscript. VP participated in the study design, collected the data, helped in the interpretation of the analyses and writing the manuscript. All authors read and approved the final manuscript.

Authors' information

Manfred S. Green is a professor in the School of Public Health at the University of Haifa. His research interests include individual immune responses to vaccines and sex differences in infectious diseases and the response to vaccines. Naama Schwartz is an epidemiologist and Victoria Peer is a PhD candidate studying aspects of sex differences in infectious diseases and vaccines under the supervision of Manfred S. Green.

Corresponding author

Correspondence to Manfred S. Green.

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Ethics approval and consent to participate

All methods were carried out in accordance with relevant guidelines and regulations. There was no collection of data from individual subjects, all human data present in this study was anonymized and no need for ethical approval. We have received exemption from the Ethics Committee of Faculty of Social Welfare & Health Sciences, University of Haifa.

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There was no use of individual data and no need for consent for publication.

Competing interests

The authors declare that they have no competing interests.

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Green, M.S., Schwartz, N. & Peer, V. Gender differences in measles incidence rates in a multi-year, pooled analysis, based on national data from seven high income countries. BMC Infect Dis 22, 358 (2022). https://doi.org/10.1186/s12879-022-07340-3

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Keywords

BMC Infectious Diseases

ISSN: 1471-2334

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