Rapid mortality transition of Pacific Islands in the 19th century

Regional autozygosity association with albumin-to-creatinine ratio reveals a novel FTO region in an Indigenous Australian population

The genetic distinctiveness of Indigenous Australian populations is well established, yet the Tiwi population remains underrepresented in genetic research. Due to their prolonged geographic isolation, these populations are prone to increased runs of homozygosity (ROH). We investigated the genetic diversity of the Tiwi population, isolated from mainland Australia for decades, based on ROH and their associations with clinical traits. We analyzed 455 whole genome sequences to identify population structure via PCA and performed a comparison with UK Biobank, Melanesian, and Polynesian cohorts. ROH assessment and genome-wide and regional measures of homozygosity were used to explore associations between clinical traits and autozygosity. Our analysis revealed distinct genetic characteristics of the Tiwi population that aligned closely with those of the Melanesian cohort. Tiwi individuals exhibited an increased burden of ROH, particularly in LINC0109, FMLN1, and RPL17P45 genes on chromosomes 2, 17, and 18, respectively, indicating prolonged isolation and genetic drift. A positive correlation was observed between genomic FROH and albumin-to-creatinine ratio (ACR) levels, suggesting a potential link between autozygosity and renal health markers. Furthermore, regional autozygosity association analysis revealed an association between elevated ACR and a region in FTO, implicating its role in obesity, kidney disease, and cardiovascular conditions. Importantly, we found that this association is strong under the recessive model. This research lays a robust foundation for further exploration of ROH mapping and its implications for disease susceptibility within Indigenous communities worldwide.

Herd immunity to endemic diseases: Historical concepts and implications for public health policy

BACKGROUND

"Herd immunity" became a contested term during the COVID-19 pandemic. Although the term "herd immunity" is often used to refer to thresholds at which some diseases can be eliminated (e.g., due to mass vaccination), the term has multiple referents. Different concepts of herd immunity have been relevant throughout the history of immunology and infectious disease epidemiology. For some diseases, herd immunity plays a role in the development of an endemic equilibrium, rather than elimination via threshold effects.

METHODS

We reviewed academic literature from 1920 to 2022, using historical and philosophical analysis to identify and develop relevant concepts of herd immunity.

RESULTS

This paper analyses the ambiguity surrounding the concept of herd immunity during the pandemic. We argue for the need to recapture a long-standing interpretation of this concept as one of the factors that leads to a dynamic endemic equilibrium between a host population and a mutating respiratory pathogen.

CONCLUSIONS

Informed by the history of infectious disease epidemiology, we argue that understanding the concept in this way will help us manage both SARS-CoV-2 and hundreds of other seasonal respiratory pathogens with which we live but which have been disrupted due to sustained public health measures/non-pharmaceutical interventions targeting SARS-CoV-2.

Extreme mortality during a historical measles outbreak on Rotuma is consistent with measles immunosuppression

Until the early twentieth century, populations on many Pacific Islands had never experienced measles. As travel to the Pacific Islands by Europeans became more common, the arrival of measles and other pathogens had devastating consequences. In 1911, Rotuma in Fiji was hit by a measles epidemic, which killed 13% of the island population. Detailed records show two mortality peaks, with individuals reported as dying solely from measles in the first and from measles and diarrhoea in the second. Measles is known to disrupt immune system function. Here, we investigate whether the pattern of mortality on Rotuma in 1911 was a consequence of the immunosuppressive effects of measles. We use a compartmental model to simulate measles infection and immunosuppression. Whilst immunosuppressed, we assume that individuals are vulnerable to dysfunctional reactions triggered by either (i) a newly introduced infectious agent arriving at the same time as measles or (ii) microbes already present in the population in a pre-existing equilibrium state. We show that both forms of the immunosuppression model provide a plausible fit to the data and that the inclusion of immunosuppression in the model leads to more realistic estimates of measles epidemiological parameters than when immunosuppression is not included.

The immunogenetic impact of European colonization in the Americas

The introduction of pathogens originating from Eurasia into the Americas during early European contact has been associated with high mortality rates among Indigenous peoples, likely contributing to their historical and precipitous population decline. However, the biological impacts of imported infectious diseases and resulting epidemics, especially in terms of pathogenic effects on the Indigenous immunity, remain poorly understood and highly contentious to this day. Here, we examine multidisciplinary evidence underpinning colonization-related immune genetic change, providing contextualization from anthropological studies, paleomicrobiological evidence of contrasting host-pathogen coevolutionary histories, and the timings of disease emergence. We further summarize current studies examining genetic signals reflecting post-contact Indigenous population bottlenecks, admixture with European and other populations, and the putative effects of natural selection, with a focus on ancient DNA studies and immunity-related findings. Considering current genetic evidence, together with a population genetics theoretical approach, we show that post-contact Indigenous immune adaptation, possibly influenced by selection exerted by introduced pathogens, is highly complex and likely to be affected by multifactorial causes. Disentangling putative adaptive signals from those of genetic drift thus remains a significant challenge, highlighting the need for the implementation of population genetic approaches that model the short time spans and complex demographic histories under consideration. This review adds to current understandings of post-contact immunity evolution in Indigenous peoples of America, with important implications for bettering our understanding of human adaptation in the face of emerging infectious diseases.

Epidemiological Isolation May Explain Differences in Historical Respiratory Infectious Disease Mortality

Indigenous and aboriginal peoples of the Americas and Pacific died at enormous rates soon after joining the global pathogen pool in the seventeenth to nineteenth centuries from respiratory infections such as smallpox, measles, and influenza. It was widely assumed that this represented a selection process against primitive societies. Darwinian selection for specific genetic resistance factors seems an unlikely hypothesis given that some populations stabilized quickly over two to three generations. European-origin populations whose childhood was marked by epidemiological isolation also suffered high infectious disease mortality from respiratory pathogens. American soldiers with smallpox, South African (Boer) children with measles, and New Zealand soldiers with influenza suggest that epidemiological isolation resulting in few previous respiratory infections during childhood may be a consistent mortality risk factor. Modern studies of innate immunity following Bacillus Calmette-Guérin (BCG) in infancy point toward rapid immune adaptation rather than evolutionary selection as an explanation for excessive first contact epidemic mortality from respiratory pathogens.

The effect of the definition of 'pandemic' on quantitative assessments of infectious disease outbreak risk

In the early stages of an outbreak, the term 'pandemic' can be used to communicate about infectious disease risk, particularly by those who wish to encourage a large-scale public health response. However, the term lacks a widely accepted quantitative definition. We show that, under alternate quantitative definitions of 'pandemic', an epidemiological metapopulation model produces different estimates of the probability of a pandemic. Critically, we show that using different definitions alters the projected effects of key parameters-such as inter-regional travel rates, degree of pre-existing immunity, and heterogeneity in transmission rates between regions-on the risk of a pandemic. Our analysis provides a foundation for understanding the scientific importance of precise language when discussing pandemic risk, illustrating how alternative definitions affect the conclusions of modelling studies. This serves to highlight that those working on pandemic preparedness must remain alert to the variability in the use of the term 'pandemic', and provide specific quantitative definitions when undertaking one of the types of analysis that we show to be sensitive to the pandemic definition.

Accounting for cross-immunity can improve forecast accuracy during influenza epidemics

Previous exposure to influenza viruses confers cross-immunity against future infections with related strains. However, this is not always accounted for explicitly in mathematical models used for forecasting during influenza outbreaks. We show that, if an influenza outbreak is due to a strain that is similar to one that has emerged previously, then accounting for cross-immunity explicitly can improve the accuracy of real-time forecasts. To do this, we consider two infectious disease outbreak forecasting models. In the first (the "1-group model"), all individuals are assumed to be identical and cross-immunity is not accounted for. In the second (the "2-group model"), individuals who have previously been infected by a related strain are assumed to be less likely to experience severe disease, and therefore recover more quickly, than immunologically naive individuals. We fit both models to estimated case notification data (including symptomatic individuals as well as laboratory-confirmed cases) from Japan from the 2009 H1N1 influenza pandemic, and then generate synthetic data for a future outbreak by assuming that the 2-group model represents the epidemiology of influenza infections more accurately. We use the 1-group model (as well as the 2-group model for comparison) to generate forecasts that would be obtained in real-time as the future outbreak is ongoing, using parameter values estimated from the 2009 epidemic as informative priors, motivated by the fact that without using prior information from 2009, the forecasts are highly uncertain. In the scenario that we consider, the 1-group model only produces accurate outbreak forecasts once the peak of the epidemic has passed, even when the values of important epidemiological parameters such as the lengths of the mean incubation and infectious periods are known exactly. As a result, it is necessary to use the more epidemiologically realistic 2-group model to generate accurate forecasts. Accounting for cross-immunity driven by exposures in previous outbreaks explicitly is expected to improve the accuracy of epidemiological modelling forecasts during influenza outbreaks.

Surveillance strategies for the detection of disease outbreaks in the Pacific islands: meta-analysis of published literature, 2010-2019

OBJECTIVE

Due to their tropical location, development status and the limited capacity of health systems, Pacific island counties and territories are particularly susceptible to infectious disease outbreaks; but evidence as to the optimal way in which outbreaks are detected is scarce. In this review, we synthesise evidence from literature about how outbreaks are detected in Pacific island countries and territories and critique factors identified as inhibiting surveillance practice.

METHOD

For this systematic review, we searched electronic databases Embase, Global Health, MEDLINE and MEDLINE Epub from 1 January 2010 and 31 March 2019 for reports describing infectious disease outbreaks occurring in the Pacific islands. Reports were included if they reported the method by which an outbreak was detected or the time between an outbreak's onset and its detection. We extracted information about the report type and authors, the outbreak and its method/s of detection, and pertinent issues inhibiting surveillance practice.

RESULTS

Of 860 articles identified, 37 reports describing 39 outbreaks met the inclusion criteria. Most outbreaks (n = 30) were identified through formal event-based surveillance; six through syndromic surveillance; and two by ad hoc notification from the community. Barriers to early outbreak detection included population isolation; lack of resources and infrastructure to support surveillance implementation and signal investigation; and broader health system factors such as preparedness planning and availability of laboratory services.

CONCLUSION

Most surveillance-related gain in the Pacific islands may be made through building formal event-based surveillance systems and streamlining reporting processes to facilitate outbreak notification. This observation is pertinent given the focus on establishing and expanding syndromic surveillance approaches for outbreak detection in the islands over the last decade.

Increased frequency of travel in the presence of cross-immunity may act to decrease the chance of a global pandemic

The high frequency of modern travel has led to concerns about a devastating pandemic since a lethal pathogen strain could spread worldwide quickly. Many historical pandemics have arisen following pathogen evolution to a more virulent form. However, some pathogen strains invoke immune responses that provide partial cross-immunity against infection with related strains. Here, we consider a mathematical model of successive outbreaks of two strains-a low virulence (LV) strain outbreak followed by a high virulence (HV) strain outbreak. Under these circumstances, we investigate the impacts of varying travel rates and cross-immunity on the probability that a major epidemic of the HV strain occurs, and the size of that outbreak. Frequent travel between subpopulations can lead to widespread immunity to the HV strain, driven by exposure to the LV strain. As a result, major epidemics of the HV strain are less likely, and can potentially be smaller, with more connected subpopulations. Cross-immunity may be a factor contributing to the absence of a global pandemic as severe as the 1918 influenza pandemic in the century since. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.

Epidemiological Isolation as an Infection Mortality Risk Factor in U.S. Soldiers from Late Nineteenth to Early Twentieth Centuries

It remains uncertain why most infectious disease mortalities disappeared before modern medical interventions. Historical epidemiology using prospectively collected U.S. Army data from the Civil War (1860-1861), Spanish-American War (1898-1899), and First World War (1917-1918) suggests that epidemiological isolation was a major mortality risk factor for soldiers. Morbidity and mortality due to common infections decreased progressively from 1860 to 1918, except for influenza during the 1918 pandemic. Adult measles or mumps infections are indicative of isolated rural populations and correlated with disease mortality by U.S. state. Experiencing infections before adulthood may equip the immune system to better resist infections and decrease mortality rates.

Breastfeeding and the Risk of Infant Illness in Asia: A Review

Infancy remains the most vulnerable period of human life for death, illness, and establishing a lifetime trajectory of growth and health. It is estimated that there are 5.3 million deaths under five years of age worldwide and approximately 800,000 lives could be saved by improving breastfeeding rates and duration. In Asia, an estimated 300,000-350,000 child deaths could be prevented with optimal breastfeeding and the majority would be under 12 months of age. We present a systematic review of studies of infection and breastfeeding in infants in Asia and further review interactions of selected infectious diseases and breastfeeding. Initially, 2459 records of possible interest were identified, 153 full text papers were reviewed in detail, and 13 papers describing diarrhoeal disease and/or acute respiratory tract infection were selected for inclusion in the review. Additional papers were selected to discuss specific diseases and their relationship to breastfeeding. The review found that a variety of methods were used with differing definitions of breastfeeding and diseases. Overall, breastfeeding when compared to the use of infant formula, is associated with significantly lower rates of diarrhoeal disease and lower respiratory tract infection, with a reduction of 50% or more to be expected, especially in infants under six months of age. The relationship between breastfeeding and specific diseases including measles and HTLV1 were reviewed. Breastfeeding reduces some disease rates, but there remain a few conditions where breastfeeding may be contra-indicated.

Fluctuating and Geographically Specific Selection Characterize Rapid Evolution of the Human KIR Region

The killer-cell immunoglobulin-like receptor (KIR) region comprises a fast-evolving family of genes that encode receptors for natural killer (NK) cells and have crucial role in host defense. Evolution of KIR was examined in the context of the human genome. Gene-content diversity and single nucleotide polymorphisms (SNP) in the KIR genes and flanking regions were compared to >660,000 genome-wide SNPs in over 800 individuals from 52 populations of the human genome diversity panel (HGDP). KIR allelic diversity was further examined using next generation sequencing in a subset of 56 individuals. We identified the SNP rs587560 located in KIR3DL3 as a marker of KIR2DL2 and KIR2DL3 and, consequently, Cen A and Cen B haplotypes. We also show that combinations of two KIR2DL4 SNPs (rs35656676 and rs592645) distinguish KIR3DL1 from KIR3DS1 and also define the major KIR3DL1 high- and low-expressing alleles lineages. Comparing the diversity of the SNPs within the KIR region to remainder of the genome, we observed a high diversity for the centromeric KIR region consistent with balancing selection (p < 0.01); in contrast, centromeric KIR diversity is significantly reduced in East Asian populations (p < 0.01), indicating purifying selection. By analyzing SNP haplotypes in a region spanning ~500 kb that includes the KIR cluster, we observed evidence of strong positive selection in Africa for high-expressing KIR3DL1 alleles, favored over the low-expressing alleles (p < 0.01). In sharp contrast, the strong positive selection (p < 0.01) that we also observed in the telomeric KIR region in Oceanic populations tracked with a high frequency of KIR3DS1. In addition, we demonstrated that worldwide frequency of high-expression KIR3DL1 alleles was correlated with virus with virus (r = 0.64, p < 10⁻⁶) and protozoa (r = 0.69, p < 10⁻⁶) loads, which points to selection globally on KIR3DL1 high-expressing alleles attributable to pathogen exposure.