The child mortality rate in the United States, for children under the age of five, was 462.9 deaths per thousand births in 1800. This means that for every thousand babies born in 1800, over 46 percent did not make it to their fifth birthday. Over the course of the next 220 years, this number has dropped drastically, and the rate has dropped to its lowest point ever in 2020 where it is just seven deaths per thousand births. Although the child mortality rate has decreased greatly over this 220 year period, there were two occasions where it increased; in the 1870s, as a result of the fourth cholera pandemic, smallpox outbreaks, and yellow fever, and in the late 1910s, due to the Spanish Flu pandemic.

The child mortality rate in the United Kingdom, for children under the age of five, was 329 deaths per thousand births in 1800. This means that approximately one in every three children born in 1800 did not make it to their fifth birthday. Over the course of the next 220 years, this number has dropped drastically, particularly in the first half of the twentieth century, and the rate has dropped to its lowest point ever in 2020 where it is just four deaths per thousand births.

This collection contains five modified data sets with mortality, population, and other demographic information for five American cities (Baltimore, Maryland; Boston, Massachusetts; New Orleans, Louisiana; New York City (Manhattan only), New York; and Philadelphia, Pennsylvania) from the early 19th century to the early 20th century. Mortality was represented by an annual crude death rate (deaths per 1000 population per year). The population was linearly interpolated from U.S. Census data and state census data (for Boston and New York City). All data sets include variables for year, total deaths, census populations, estimated annual linearly interpolated populations, and crude death rate. The Baltimore data set (DS0001) also provides birth and death rate variables based on race and slave status demographics, as well as a variable for stillbirths. The Philadelphia data set (DS0005) also includes variables for total births, total infant deaths, crude birth rate, and infant deaths per 1,000 live births.

The child mortality rate in Germany, for children under the age of five, was 340 deaths per thousand births in 1800. This means that more than one in every three children born in 1800 did not make it to their fifth birthday. Child mortality increased to almost fifty percent in the mid-nineteenth century, as the country industrialized and urbanized rapidly, which allowed diseases to spread much faster. This changed however, with the introduction of mandatory vaccination in 1874, which kickstarted a gradual decline in child mortality in Germany. The decline was most rapid in the first half of the twentieth century, and by the year 2020 child mortality in Germany is expected to be as low as four deaths per thousand births.

The child mortality rate in France, for children under the age of five, was 412 deaths per thousand births in 1800. This means that more than forty percent of all children born in 1800 did not make it to their fifth birthday. Child mortality remained high in the nineteenth century, before falling at a much faster rate throughout the 1900s. Despite falling consistently during the last 130 years, there were two occasions where child mortality actually increased, which can be attributed to both World Wars and the Spanish Flu Pandemic. In 2020, the child mortality rate in France is expected to be just four deaths per thousand births.

The child mortality rate in Canada, for children under the age of five, was 333 deaths per thousand births in the year 1830. This means that one third of all children born in 1830 did not make it to their fifth birthday. Child mortality remained above 25 percent for the remainder of the nineteenth century, before falling at a much faster rate throughout the 1900s. By the year 2020, Canada's child mortality rate is expected to be just five deaths per thousand births.

The study’s theme: The development of infant mortality in Germany for the 19th century is only poorly documented. Especially for the period prior to 1871 only small area statistics are available. With the preparation of the information collected by the authorities of the former German States the author tries to create a new statistical basis. The reconstructed national series of birth and infant mortality (from 1826) documents relatively high infant mortality rates with little progress (i.e. improvement of the situation) until the beginning of the 20th Century. Considering the influence of urbanization the evaluation of the different regional patterns and trends leads to a new weighting of the problem. Thus the living and working conditions in the country were of considerable importance. Overall, the prevailing habits and attitudes are considered crucial to the survival of small children (Gehrmann 2011, S. 807)

Data and data preparation, source problems: The federal structure of the Empire leads to the problem that the printed statistics on infant mortality before 1901 remained incomplete. In some German states, information concerning infant mortality was not collected from the beginning of the registry offices. However, the ‘Kaiserliches Statistisches Amt’ (Imperial Statistical Office) was able to create despi9te the difficult situation a life table, which represented 97,3% of live birth for the period of 1872 to 1880. Hence, the annual infant mortality rate in 1872 is known. „Die föderale Struktur des Kaiserreichs hatte (…) zur Folge, dass die gedruckte Statistik zur Säuglingssterblichkeit vor 1901 lückenhaft blieb. Mehr noch: es wurden offensichtlich in einigen Staaten diesbezügliche Angaben gar nicht oder zumindest nicht von Anfang an bei den Standesämtern abgefragt. Als das Kaiserliche Statistische Amt in den 1880er Jahren die erste Sterbetafel für das Deutsche Reich erstellen wollte, musste es deshalb konstatieren, dass in den Einzelstaaten „fast alle in der Statistik überhaupt üblichen Arten und Grade der Spezialisierung vertreten“ (Kaiserliches Statistisches Amt 1887: 21) waren, aus manchen aber trotzdem keine geeigneten Unterlagen beschafft werden konnten. Immerhin repräsentierte die Sterbetafel am Ende doch 96,8% der Reichsbevölkerung im Jahre 1885 und 97,3% der Lebendgeborenen 1872 bis 1880. Damit ist auch die jährliche Säuglingssterblichkeitsrate ab 1872 bekannt. (…) Mit Hilfe des Sterbetafel-Materials kann die statistische Reihe aus „Bevölkerung und Wirtschaft“ also um fast 30 Jahre nach hinten verlängert werden. (…) Komplizierter stellt sich die Sachlage für weiter zurückliegende Zeitabschnitte dar. „ (S. 812-813) Although in most German states statistical collection on population movement has been carried out, the statistics vary considerably in quality. In the first step therefore, the author reject the procedure of simply extrapolating the birth rates because of the qualitative differences of the early statistics are too fundamental. Especially, in this approach of simply summing up, the values of the undocumented areas would equate with the values of the other well documented regions. Therefore, the author chose a complex way to estimate the lacking values: The missing values in small territories are estimated on the basis of the values of neighboring regions. Finally, it can be seen, that the data for the period from 1828 to 1871, calculated by the complex procedure of filling in missing data does not lead to significantly different results comparing to the data row calculated by the simple sum of the different sources. Per year, the difference between the two series (the series calculated in the complex way and the series calculated by summing up the values of the available statistics) is not more than 0,9 percent points, which can be seen as a slight difference between the two series in relation to the former level of infant mortality. The indeterminate values of those German states lacking a birth statistics may not being significantly different to those calculated on the basis of the complex procedure, because even unexpected, extreme runaway values in individual states can not realistically assumed to be so large that they could have a sufficient impact on the overall values. Thus, the presented row is a solid basis for the assessment of the overall development of the German Empire’s birth development. „Vielmehr empfiehlt es sich, zunächst in kleinen Schritten für die einzelnen Territor...

The child mortality rate in Afghanistan (for children under the age of five) was around 475 deaths per 1000 births during the course of 19th century. Given as a percentage, this means that 47.5% of children born would not make it to their 5th birthday. After 1950, the child morality rate dropped significantly due to considerable medical advancements, falling to 68 deaths per thousand in 2020. Despite this considerable decline in recent decades, Afghanistan still has one of the highest child mortality rates in the world. Afghanistan's infant mortality rate (among those aged below one year) in 2020 is 52 deaths per thousand births, meaning that the majority of child deaths occur during infancy.

In the mid-19th century, the urban milk supply in the United States was regularly skimmed or diluted with water, reducing its nutritional value. At the urging of public health experts, cities across the country hired milk inspectors, who were tasked with collecting and analyzing milk samples with the goal of preventing adulteration and skimming. Using city-level data for the period 1880-1910, we explore the effects of milk inspections on infant mortality and mortality among children under the age of 5. Event-study estimates are small and statistically insignificant, providing little evidence of post-treatment reductions in either infant or child mortality.

The child mortality rate in Austria, for children under the age of five, was 387 deaths per thousand births in 1800. This means that just under forty percent of all children born in 1860 did not make it to their fifth birthday. Child mortality increased to over forty percent for most of the nineteenth century, as the country became more industrialized and urbanized, which allowed diseases to spread much faster. From 1900 onwards, the child mortality rate in Austria dropped consistently until today, (apart from a small increase during the Second World War) and it is expected to fall to just four deaths per thousand births in 2020.

ICD10h2024.2 (this version, published June 2025) incorporates the following changes: - Manual: new preface to list changes to files; changes relating to code changes; a small number of other corrections and improvements. - Masterlist (see 2025MasterlistChanges): 9 new codes added, 5 codes deleted, and 17 changes made to ICD10 or ICD10h descriptions. - Transferfile (see 2025TransferfileChanges): 47 errors were fixed. - InfantCat (see 2025InfantCatChanges): 17 ICD10h codes were updated. - Historic Strings English (see 2025HistoricStringsEnglishChanges): 14 changes were made to ICD10h or ICD10hInjury codes were made. ICD10hDescription and ICD10hInjuryDescription columns were deleted.

This file contains manual for ICD10h: a historic cause of death coding and classification scheme for individual-level causes of death. ICD10h has been designed by the authors to aid the coding and classification of causes of death recorded on historic individual death records. Input data for the scheme consisted of mortality records for Scottish town of Kilmarnock and Isle of Skye (derived from the project Determining the Demography of Victorian Scotland Through Record Linkage, ESRC RES-000-23-0128 held at the Cambridge Group for the History of Population and Social Structure, University of Cambridge), and the island of Tasmania (P. Gunn and R. Kippen, ‘Household and Family Formation in Nineteenth-Century Tasmania, Dataset of 195 Thousand Births, 93 Thousand Deaths and 51 Thousand Marriages Registered in Tasmania, 1838-1899’, 2008) for the late 19th century. Although ICD10h contains exemplar causes of death based on these datasets, it does not contain any information about any deceased person apart from cause of death, and does not provide counts of deaths from particular causes. The data were hand-coded and subject to stringent algorithm-assisted tests. The ICD10h system is based on the 10th revision of the International Classification of Diseases - 2016 version (ICD10 - 2016), and combines ICD10 codes (without modification) with new codes for archaic/historic terms. A general historical classification of deaths, HistCat, is also provided, as well as a historical classification for infant deaths, InfantCat. The manual presents the background to the development of the system, and explains how to use the system for the coding and classification of causes in both English and other languages. It is associated with additional datasets (available in both .xlsx and .csv) containing 1) the lists of codes and their descriptions which constitute the coding and classification system, together with the HistCat classification [https://doi.org/10.17863/CAM.109961]; 2) a set of exemplar historic strings in the English language [https://doi.org/10.17863/CAM.109962]; and 3) the classification for infant deaths [https://doi.org/10.17863/CAM.109963]. ICD10h has been developed in association with the following research projects: Digitising Scotland/Scottish Health Informatics Project (funded by the ESRC); Studying Health in Port Cities (funded by The Netherlands Organisation for Scientific Research); the Great Leap (funded by COST-Action CA22116). Please note that ICD10h is a research tool created to facilitate the study of historical cause of death records and should not be used for any official purpose. It is based on the International Classification of Diseases, 10th Revision (ICD-10) version 2016 (Geneva: World Health Organization 2016) but is not a recognised version or extension of ICD-10 and is not authorised by WHO. However we have consulted with WHO: they recognise that ICD10h is a useful academic methodology and have not raised any objections to its creation. Data coded using ICD10h are not directly comparable with data coded in ICD-10, and the underlying or primary cause of death derived using the ICD10h methodology may be different from the underlying cause derived in ICD-10 according to the WHO rules. Please note that ICD-10 version 2016 is not the most recent version of ICD-10; and that WHO now recommend the use of ICD-11; a more advanced and detailed classification.

This depository includes the replication package for Interest Rates, Sanitation Infrastructure, and Mortality Decline in Nineteenth-Century England and Wales, to be published in the Journal of Economic History in March 2022. Abstract: This paper investigates whether high borrowing costs deterred investment in sanitation infrastructure in late nineteenth-century Britain. Town councils had to borrow to fund investment, with considerable variation in interest rates across towns and over time. Panel regressions, using annual data from more than 800 town councils, indicate that higher interest rates were associated with lower levels of infrastructure investment between 1887 and 1903. Instrumental variable regressions show that falling interest rates after 1887 stimulated investment and led to lower infant mortality. These findings suggest that Parliament could have expedited mortality decline by subsidizing loans or facilitating private borrowing.

By the early 1870s, the child mortality rate of the area of modern-day Bangladesh was estimated to be just over five hundred deaths per thousand live births, meaning that more than half of all infants born in these years would not survive past their fifth birthday. Child mortality would steadily climb towards the end of the 19th century, to a rate of almost 57 percent, as a series of famines would result in significant declines in access to nutrition and the increased displacement of the population. However, after peaking at just over 565 deaths per thousand births at the turn of the century, the British colonial administration partitioned the Bengal region (a large part of which lies in present-day India), which would begin to bring some bureaucratic stability to the region, improving healthcare and sanitation.

Child mortality would largely decline throughout the 20th century, with two temporary reversals in the late 1940s and early 1970s. The first of these can be attributed in part to disruptions in government services and mass displacement of the country’s population in the partitioning of India and Pakistan following their independence from the British Empire; during which time, present-day Bangladesh became East Pakistan. The second reversal would occur in the early 1970s, as a side effect for the Bangladesh Liberation War, the famine of 1974, and the subsequent transition to independence. Outside of these reversals, child mortality would decline significantly in the 20th century, and by the turn of the century, child mortality in Bangladesh would fall below one hundred deaths per thousand births; less than a fifth of the rate at the beginning of the century. In the past two decades, Bangladesh's child mortality has continued its decline to roughly a third of this rate, due to improvements in healthcare access and quality in the country; in 2020, it was estimated that for every thousand children born in Bangladesh, almost 97 percent will survive past the age of five years.

Sources: Conscription lists of the birth cohorst 1813-1842, Department II, - of the capital and royal seat Munich, - of the royal county court Toelz and - of the public records office of Munich. Reichenhall: conscription lists are available only for the birth cohort 1840. Districts Miesbach, Toelz, Wasserburg and Reichenhall: all available conscription lists of the public records office are evaluated and all inductees of the birth cohorts 1813 to 1842 are collected.

This file contains the exemplar list of historic strings together with the ICD10h codes and descriptions associated with the ICD10h (Historic cause of death coding and classification scheme for individual-level causes of death). ICD10h has been designed by the authors to aid the coding and classification of causes of death recorded on historic individual death records and associated files include a manual, the list of codes, descriptions and values of a general categorisation, and a categorisation for infant mortality. The ICD10h system is based on the 10th revision of the International Classification of Diseases - 2016 version (ICD10 - 2016), and combines ICD10 codes (without modification) with new codes for archaic/historic terms.

The data was derived from the following projects/deposited data: Determining the Demography of Victorian Scotland Through Record Linkage, ESRC RES-000-23-0128 held at the Cambridge Group for the History of Population and Social Structure, University of Cambridge; P. Gunn and R. Kippen, ‘Household and Family Formation in Nineteenth-Century Tasmania, Dataset of 195 Thousand Births, 93 Thousand Deaths and 51 Thousand Marriages Registered in Tasmania, 1838-1899’, 2008.

The resource creation was supported by the following projects: Digitising Scotland/Scottish Health Informatics Project (funded by the ESRC); Studying Health in Port Cities (funded by The Netherlands Organisation for Scientific Research); The Great Leap (funded by COST-Action CA22116).

SHARING/ACCESS INFORMATION

This resource is available under a CC BY licence.

Recommended citation for this dataset: Historic cause of death coding and classification scheme for individual-level causes of death – English language historic strings [https://doi.org/10.17863/CAM.109962]

Please see the associated resources: Historic cause of death coding and classification scheme for individual-level causes of death – manual [https://doi.org/10.17863/CAM.109960] Historic cause of death coding and classification scheme for individual-level causes of death – Codes [https://doi.org/10.17863/CAM.109961] Historic cause of death coding and classification scheme for individual-level causes of death – Infant Categorisations [https://doi.org/10.17863/CAM.109963]

ICD10h is a research tool created to facilitate the study of historical cause of death records and should not be used for any official purpose. It is based on the International Classification of Diseases, 10th Revision (ICD-10) version 2016 (Geneva: World Health Organization 2016) but is not a recognised version or extension of ICD-10 and is not authorised by WHO. However we have consulted with WHO: they recognise that ICD10h is a useful academic methodology and have not raised any objections to its creation. Data coded using ICD10h are not directly comparable with data coded in ICD-10, and the underlying or primary cause of death derived using the ICD10h methodology may be different from the underlying cause derived in ICD-10 according to the WHO rules. Please note that ICD-10 version 2016 is not the most recent version of ICD-10; and that WHO now recommend the use of ICD-11; a more advanced and detailed classification.

DATA & FILE OVERVIEW

ICD10h_HistoricStringsEnglish.xlsx Excel file consisting of 2 worksheets: 1) ReadMe sheet 2) HistoricStringsEnglish

Separate csv file for 2) containing the same information.

This file builds on a previous, unpublished version of ICD10h (dating from 2020).

METHODOLOGICAL INFORMATION

The data were hand-coded and subject to stringent algorithm-assisted tests.

DATA-SPECIFIC INFORMATION FOR: HistoricStringsEnglish

Number of variables: 7

Number of cases/rows: 3306

Variable List: ID_HistoricStrings (unique ID for HistoricStrings table) HistoricString (Historic cause of death string as encountered in records) ICD10h (ICD10h code) ICD10hInjury (additional ICD10h code for injuries) ICD10hDescription (ICD10h description) ICD10hInjuryDescription (additional ICD10h description for injuries) CancerMalignancyFlag (0=not a neoplasm; 1=no information on malignancy; 2=stated to be malignant; 3=stated to be benign; 4=stated to be of uncertain behaviour)

This file contains the infant death categorisations associated with the ICD10h (Historic cause of death coding and classification scheme for individual-level causes of death). ICD10h has been designed by the authors to aid the coding and classification of causes of death recorded on historic individual death records and associated files include a manual, the list of codes, descriptions and values of a general categorisation, and exemplar list of historic strings together with the ICD10h codes. The ICD10h system is based on the 10th revision of the International Classification of Diseases - 2016 version (ICD10 - 2016), and combines ICD10 codes (without modification) with new codes for archaic/historic terms.

The data was derived from the following projects/deposited data: Determining the Demography of Victorian Scotland Through Record Linkage, ESRC RES-000-23-0128 held at the Cambridge Group for the History of Population and Social Structure, University of Cambridge; P. Gunn and R. Kippen, ‘Household and Family Formation in Nineteenth-Century Tasmania, Dataset of 195 Thousand Births, 93 Thousand Deaths and 51 Thousand Marriages Registered in Tasmania, 1838-1899’, 2008.

The resource creation was supported by the following projects: Digitising Scotland/Scottish Health Informatics Project (funded by the ESRC); Studying Health in Port Cities (funded by The Netherlands Organisation for Scientific Research); The Great Leap (funded by COST-Action CA22116).

SHARING/ACCESS INFORMATION

This resource is available under a CC BY licence.

Recommended citation for this dataset: Alice Reid, Eilidh Garrett, Maria Hiltunen Maltesdotter, Angelique Janssens, 2024, ICD10h: Historic cause of death coding and classification scheme for individual-level causes of death – Infant Categorisations [https://doi.org/10.17863/CAM.109963]

Please see the associated resources: Historic cause of death coding and classification scheme for individual-level causes of death – manual [https://doi.org/10.17863/CAM.109960] Historic cause of death coding and classification scheme for individual-level causes of death – Codes [https://doi.org/10.17863/CAM.109961] Historic cause of death coding and classification scheme for individual-level causes of death – English language historic strings [https://doi.org/10.17863/CAM.109962]

ICD10h is a research tool created to facilitate the study of historical cause of death records and should not be used for any official purpose. It is based on the International Classification of Diseases, 10th Revision (ICD-10) version 2016 (Geneva: World Health Organization 2016) but is not a recognised version or extension of ICD-10 and is not authorised by WHO. However we have consulted with WHO: they recognise that ICD10h is a useful academic methodology and have not raised any objections to its creation. Data coded using ICD10h are not directly comparable with data coded in ICD-10, and the underlying or primary cause of death derived using the ICD10h methodology may be different from the underlying cause derived in ICD-10 according to the WHO rules. Please note that ICD-10 version 2016 is not the most recent version of ICD-10; and that WHO now recommend the use of ICD-11; a more advanced and detailed classification.

DATA & FILE OVERVIEW

ICD10h_InfantCat.xlsx Excel file consisting of 2 worksheets: 1) ReadMe sheet 2) InfantCat

Separate csv file for 2) containing the same information.

This file builds on a previous, unpublished version of ICD10h (dating from 2020). InfantCat2024 provides an updated version of the previous categorisation (InfantCat2020). Please see the Manual for detail of the changes.

METHODOLOGICAL INFORMATION

The data were hand-coded and subject to stringent algorithm-assisted tests.

DATA-SPECIFIC INFORMATION FOR: InfantCat

Number of variables: 4

Number of cases/rows: 14088

Variable List: IDMasterlist (unique ID number, same as Masterlist table) ICD10h (ICD10h code ) Infantcat2024 (Infantcat2024 category) Infantcat2020 (Infantcat2020 category)

This dataset contains a variety of demographic measures (related to fertility, marriage, mortality and migration), plus a range of socio-economic indicators (related to households, age structure, and social class) for the 2000+ Registration Sub Districts (RSDs) in England and Wales for each census year between 1851 and 1911, and for the 600+ Registration Districts of Scotland 1851-1901. The measures have mainly been derived from the computerised individual level census enumerators' books (and household schedules for 1911) enhanced under the I-CeM project. I-CeM does not currently include data for England and Wales 1871, although the project has been able to access a version of the data for that year it does not contain information necessary to calculate many of the variables presented here. Scotland 1911 is also not available. Users should therefore beware that 1871 does not contain data for many of the variables. Additional data has been derived from the tables summarising numbers of births and deaths by year and areas, which were published by the Registrar General of England and Wales in his quarterly, annual and decennial reports of births, deaths and marriages. Data from the decennial reports was obtained from Woods (SN 3552) and we transcribed data from the quarterly and annual reports ourselves. Counts of births and deaths for Scottish Registration Districts were obtained from the Digitising Scotland project at the University of Edinburgh. The dataset builds on SN 8613 and SN 853547 which provide data for a more limited set of variables and for England and Wales only (the same dataset also has two UKDS SN numbers as it was re-routed by UKDS during the deposit process).

This project will present the first historic population geography of Great Britain during the late nineteenth century. This was a period of unprecedented demographic change, when both mortality and fertility started the dramatic secular declines of the first demographic transition. National trends are well established: mortality decline started in childhood and early adulthood, with infant mortality lagging behind, particularly in urban-industrial areas. The fall in fertility was led by the middle classes but quickly spread throughout society. Urban growth was fuelled by movement from the countryside to the city, but there was also considerable migration overseas, particularly from Scotland, although to some extent outmigration was offset by immigration. There was local and regional variation in these patterns, and a contrast between the demographic experiences of Scotland and of England and Wales. Marriage was later in Scotland but fertility within marriage higher, and the improvement in Scottish mortality was slower than that south of the border. However, while there has been research on local and regional patterns within each country, these have mainly been pursued separately, and it is therefore unclear whether there were real national differences or whether there were local demographic continuities across borders, and if so whether they followed economic, occupational, cultural or even linguistic lines. Understanding population processes involves a holistic appreciation of the interaction between the basic demographic components of fertility, mortality, nuptiality and migration, and how they come together, interacting with economic and cultural processes, to create a specific demographic system via the spread of people and ideas. This project is the first to consider a historical population geography of the whole of Great Britain across the first demographic transition, drawing together measures of nuptiality, fertility, mortality and migration for small geographic areas and unpacking how they interacted to produce the more readily available broad-brush national patterns for Scotland and for England and Wales.

We will build on our immensely successful project on the fertility of Victorian England and Wales, which used complete count census data for England and Wales to calculate more detailed fertility measures than ever previously possible for some 2000 small geographic areas and 8 social groups, allowing the investigation of intra-urban as well as urban-rural differences in fertility. The new measures allowed us to examine age patterns of fertility across the two countries for the first time. We were also able to calculate contextual variables from the census data which allowed us to undertake spatial analysis of the influences on fertility over time. As well as academic papers, our previous project presented summary data at a fine spatial resolution in an interactive online atlas, populationspast.org, a major new resource which is already being widely used as a teaching tool in both schools and universities.

In this new project we will calculate comparable measures of fertility and contextual variables using the full count census data for Scotland, 1851 to 1901 inclusive, to complement those for England and Wales. However, our new project will go considerably further and will integrate place-specific measures of mortality and migration, for both Scotland and for England and Wales. We will provide new age-specific data on fertility, mortality and migration for the whole of Great Britain using existing datasets, at a finer geographic level than has previously been possible, and will analyse these spatially and temporally to gain a panoramic understanding of the forces driving this crucial period of demographic and social change. We will expand populationspast.org to bring our new findings to a wide academic and non-academic audience and will provide the data for others to explore interactively.

The objective of this study is to describe the clinical presentations, radiological and laboratory findings, and outcomes of COVID-19 disease in infants ≤ 90 days of age at presentation. We conducted a retrospective study of infants in this age group who were found to be SARS-CoV-2 positive. Asymptomatic infants who were identified through routine testing following delivery to COVID-19-positive mothers were excluded. We classified infants according to their presentation: asymptomatic, mildly symptomatic, moderately symptomatic, and severely/critically symptomatic. A total of 36 infants were included. Of them, two were asymptomatic and four had severe/critical presentation. Of the severely symptomatic infants, two were considered as multisystem inflammatory syndrome in children (MIS-C) and there was one death. One infant in the severe symptomatic group presented with cardiac failure, with the possibility of congenital infection. Another infant presented with cardiogenic shock. None of these infants received antiviral medication. The study found that infants ≤ 90 days can present with a severe form of COVID-19 disease. Multisystem inflammatory syndrome in children, although rarely reported in infants, is a possible complication of COVID-19 disease and can be associated with significant morbidity and mortality.

The child mortality rate in the Netherlands, for children under the age of five, was 324 deaths per thousand births in 1800. This means that just under one third of all children born in 1860 did not make it to their fifth birthday. Child mortality reached its highest recorded level in the Netherlands in the late nineteenth century, as rapid industrialization led to increased urbanization, which in turn allowed diseases to spread much faster, although it did decrease from 1875 until today. The only times where the rate deviated were in the 1910s and 1940s, due to the Spanish Flu pandemic and the Second World War. By 2020, the child mortality rate of the Netherlands is expected to be just three deaths per thousand.

Health improved in English cities in the last third of the nineteenth century, in tandem with substantial increases in public spending on water supplies and sanitation. However previous efforts to measure the contribution of public expenditures to mortality improvements have been hampered by difficulties in quantifying public health investments, and the lack of mortality data for specifically urban populations. We improve upon the existing evidence base by (1) creating measures of the stock of Urban District sanitary capital, by type, based on capital expenditure flows, rather than loan stocks; (2) using mortality and capital stock data that relate to the same administrative units (Urban Districts); and (3) studying the period 1880-1909 as well as the earlier period from 1845. The stock of sewerage capital was robustly related to improvements in all-cause mortality after 1880. The size of this effect varied with the extent of public investment in water supplies, suggesting complementary between the two assets. For the period 1845-1884 investments in water were associated with declines in infant and child mortality but the effect was much smaller and less precisely estimated in later decades. Our results suggest that improvements in water and sewerage targeted different transmission pathways for faecal-oral diseases. This deposit contains the data and code needed to replicate the results in the paper.