Spatial growth rate of emerging SARS-CoV-2 lineages in England, September 2020-December 2021.

This paper uses a robust method of spatial epidemiological analysis to assess the spatial growth rate of multiple lineages of SARS-CoV-2 in the local authority areas of England, September 2020-December 2021. Using the genomic surveillance records of the COVID-19 Genomics UK (COG-UK) Consortium, the analysis identifies a substantial (7.6-fold) difference in the average rate of spatial growth of 37 sample lineages, from the slowest (Delta AY.4.3) to the fastest (Omicron BA.1). Spatial growth of the Omicron (B.1.1.529 and BA) variant was found to be 2.81× faster than the Delta (B.1.617.2 and AY) variant and 3.76× faster than the Alpha (B.1.1.7 and Q) variant. In addition to AY.4.2 (a designated variant under investigation, VUI-21OCT-01), three Delta sublineages (AY.43, AY.98 and AY.120) were found to display a statistically faster rate of spatial growth than the parent lineage and would seem to merit further investigation. We suggest that the monitoring of spatial growth rates is a potentially valuable adjunct to outbreak response procedures for emerging SARS-CoV-2 variants in a defined population.

Operation Pied Piper: a geographical reappraisal of the impact of wartime evacuation on scarlet fever and diphtheria rates in England and Wales, 1939-1945.

This paper examines the geographical impact of the British Government's wartime evacuation scheme on notified rates of two common acute childhood diseases (scarlet fever and diphtheria) in the 1470 local government districts of England and Wales, 1939-1945. Drawing on the notifications of communicable diseases collated by the General Register Office (GRO), we establish pre-war (baseline) disease rates for the 1470 districts. For the war years, techniques of binary logistic regression analysis are used to assess the associations between (a) above-baseline ('raised') disease rates in evacuation, neutral and reception districts and (b) the major phases of the evacuation scheme. The analysis demonstrates that the evacuation was temporally associated with distinct national and regional effects on notified levels of disease activity. These effects were most pronounced in the early years of the dispersal (1939-1941) and corresponded with initial levels of evacuation-related population change at the regional and district scales.

Predictability in a highly stochastic system: final size of measles epidemics in small populations.

A standard assumption in the modelling of epidemic dynamics is that the population of interest is well mixed, and that no clusters of metapopulations exist. The well-known and oft-used SIR model, arguably the most important compartmental model in theoretical epidemiology, assumes that the disease being modelled is strongly immunizing, directly transmitted and has a well-defined period of infection, in addition to these population mixing assumptions. Childhood infections, such as measles, are prime examples of diseases that fit the SIR-like mechanism. These infections have been well studied for many systems with large, well-mixed populations with endemic infection. Here, we consider a setting where populations are small and isolated. The dynamics of infection are driven by stochastic extinction-recolonization events, producing large, sudden and short-lived epidemics before rapidly dying out from a lack of susceptible hosts. Using a TSIR model, we fit prevaccination measles incidence and demographic data in Bornholm, the Faroe Islands and four districts of Iceland, between 1901 and 1965. The datasets for each of these countries suffer from different levels of data heterogeneity and sparsity. We explore the potential for prediction of this model: given historical incidence data and up-to-date demographic information, and knowing that a new epidemic has just begun, can we predict how large it will be? We show that, despite a lack of significant seasonality in the incidence of measles cases, and potentially severe heterogeneity at the population level, we are able to estimate the size of upcoming epidemics, conditioned on the first time step, to within reasonable confidence. Our results have potential implications for possible control measures for the early stages of new epidemics in small populations.

Abrupt transition to heightened poliomyelitis epidemicity in England and Wales, 1947-1957, associated with a pronounced increase in the geographical rate of disease propagation.

The abrupt transition to heightened poliomyelitis epidemicity in England and Wales, 1947-1957, was associated with a profound change in the spatial dynamics of the disease. Drawing on the complete record of poliomyelitis notifications in England and Wales, we use a robust method of spatial epidemiological analysis (swash-backwash model) to evaluate the geographical rate of disease propagation in successive poliomyelitis seasons, 1940-1964. Comparisons with earlier and later time periods show that the period of heightened poliomyelitis epidemicity corresponded with a sudden and pronounced increase in the spatial rate of disease propagation. This change was observed for both urban and rural areas and points to an abrupt enhancement in the propensity for the geographical spread of polioviruses. Competing theories of the epidemic emergence of poliomyelitis in England and Wales should be assessed in the light of this evidence.

Common acute childhood infections and appendicitis: a historical study of statistical association in 27 English public boarding schools, 1930-1934.

Although the involvement of common childhood infections in the aetiology of acute appendicitis has long been conjectured, supporting evidence is largely restricted to a disparate set of clinical case reports. A systematic population-based analysis of the implied comorbid associations is lacking in the literature. Drawing on a classic epidemiological dataset, assembled by the School Epidemics Committee of the United Kingdom's Medical Research Council (MRC) in the 1930s, this paper presents a historical analysis of the association between termly outbreaks of each of six common childhood infections (chickenpox, measles, mumps, rubella, scarlet fever and whooping cough) and operated cases of acute appendicitis in 27 English public boarding schools. When controlled for the potential confounding effects of school, year and season, multivariate negative binomial regression revealed a positive association between the level of appendicitis activity and the recorded rate of mumps (beta=0.15, 95% CI 0.07-0.24, P<0.001). Non-significant associations were identified between appendicitis and the other sample infectious diseases. Subject to data caveats, our findings suggest that further studies are required to determine whether the comorbid association between mumps and appendicitis is causal.

Spatial and temporal patterns in final amendments to provisional disease counts.

This article examines temporal and spatial patterns in the relationship between provisional and amended reports for Hepatitis A and Hepatitis B received from each state by the Centers for Disease Control and Prevention through the U.S. National Notifiable Diseases Surveillance System from 1980 to 1992. It demonstrates that, as the 1980s unfolded, the preliminary disease reports became less representative markers of final disease counts. Practitioners at the state and community levels need to be aware of the temporal and spatial instabilities in such provisional data if they are used to provide early warning of contemporary health aberrations.

The importance of long-term records in public health surveillance: the US weekly sanitary reports, 1888-1912, revisited.

BACKGROUND: This paper outlines the ways in which a little-used archive of early public health records may throw light on longer-term trends in international epidemic behaviour and serve as a major source of epidemiological information for historians of urbanization and public health. The Weekly Abstract of Sanitary Reports was the official disease surveillance report of the US Public Health Service and its predecessors, and began to publish urban mortality statistics on a regular basis in 1888. Here, the authors describe the first 25 years of continuous reporting (1888-1912), when the Reports contained not only disease data for US cities, but also records sent back by US consuls based in some 250 cities in many parts of the world. METHODS: The content of the weekly editions of the Reports was systematically sampled and analysed using graphical techniques and the simple statistical method of running means. RESULTS: Relatively complete weekly series of mortality from all causes, and six infectious diseases (diphtheria, enteric or typhoid fever, measles, scarlet fever, tuberculosis and whooping cough) were identified for a total of 100 cities world-wide. CONCLUSION: Reporting coverage for these cities is sufficiently complete that multivariate analysis should be possible to obtain a comparative picture of mortality for many parts of the world. Despite limitations of the data, sources of the type described in this paper form an important comparative database for studying international patterns of mortality.

The application of multidimensional scaling methods to epidemiological data.

This paper illustrates the use of multidimensional scaling methods (MDS) to examine space-time patterns in epidemic data. The paper begins by outlining the principles of MDS. The model is then formally specified and illustrated by application to two data sets. The first is partly a tutorial example. It uses monthly reported measles morbidity data for the 31-year period from January 1960 to December 1990, collected for the 50 states of the USA, plus New York City and the District of Columbia. These data are used to explore the various ways in which MDS may be used to identify changing spatial patterns in geographically-coded data. In addition to their tutorial use, the data are also employed to search for any substantive changes in the geographical structure of measles epidemics in the USA that may have followed the introduction of mass vaccination in 1965. New England appears to have developed an epidemic profile distinct from the rest of the USA, and there is tentative evidence of an urban-rural split in epidemic characteristics. The second data set takes annual reported measles mortality data for New Zealand and the states of Australia from 1860 to 1949. MDS is used to show how the spatial relationships among these geographical units have changed over time in response to changes in the sizes of local susceptible populations.

Statistical modelling of measles and influenza outbreaks.

This paper reviews the application of statistical models to outbreaks of two common respiratory viral diseases, measles and influenza. For each disease, we look first at its epidemiological characteristics and assess the extent to which these either aid or hinder modelling. We then turn to the models that have been developed to simulate geographical spread. For measles, a distinction is drawn between process-based and time series models; for influenza, it is the scale of the communities (from small groups to global populations) which primarily determines modelling style. Applications are provided from work by the authors, largely using Icelandic data. Finally we consider the forecasting potential of the models described.

The geographic structure of measles epidemics in the northeastern United States.

The incidence of disease across geographic space often produces distinctive regional patterns. In this paper, a modeling approach to the identification of the factors that shape the patterns is presented, and a procedure for fitting the model to observed data is given. The methodology is illustrated by an application to the geographic structure of measles epidemics among 22 states of the northeastern United States, New York City, and Washington, D.C., from 1962 to 1988. The patterns identified are interpreted in terms of the spatial behavior of measles epidemics in the region, and the implications of the methodology for surveillance and control are considered.

The changing geographical coherence of measles morbidity in the United States, 1962-88.

Geographical coherence may be defined as the degree to which the behaviour of a time series in one geographical area corresponds with the time series behaviour in another. This paper illustrates the concept using the epidemiological time series of reported monthly measles morbidity for the states of the United States for the 27 years from January 1962 to December 1988. Over this period, as measles morbidity has declined in response to vaccination campaigns, and as the seasonal peaking of the disease in late spring has become less pronounced, the geographical coherence has altered at the national, divisional, regional and state levels. There was a steady decline in coherence from 1962 to 1980. In 1981, a dramatic reduction occurred, but there has been some recovery since. The implications for spatial forecasting models of these reducing levels of coherence are discussed.

Seasonality in tropical AIDS: a geographical analysis.

This paper presents evidence that the growth rate of the AIDS epidemic at the district level in Uganda, Central Africa, displays a seasonally recurring geographical pattern, with epidemic acceleration in some areas of the country in the first 8 months of each year. The spatial and temporal variations in acceleration appear to be correlated with the predominant agricultural systems in different parts of Uganda. Based upon the frequently hypothesized relationship between malnourishment and the progression to clinical AIDS in HIV-infected people, it is suggested that the variations in epidemic speed reflect the seasonal patterns of nutritional deficiency which occur under some tropical agricultural systems. These preliminary findings require further verification since they have important implications for directing nutrition-related remedial responses to the AIDS epidemic in tropical countries where malnutrition and endemic HIV infection coincide.

PIP: Human geographers applied data of 12,444 cases of AIDS in Uganda diagnosed between January 1986-December 1989 to a statistical methodology used in geography to see if AIDS exhibits seasonal rhythms. The analysis revealed that seasonally recurring geographical patterns were the basis for the velocity of reported AIDS epidemics in different districts of Uganda (p.05). Epidemic acceleration was most evident in all regions of Uganda, except the Central region. The AIDS epidemic patterns paralleled the seasonal rhythms of agricultural production. In the Central region, crop production was perennial. Thus food was always available which may account for no apparent AIDS epidemic pattern in this region. On the other hand, pastoral activity and annual arable crop production predominated in the Eastern region where constant fluctuations in AIDS incidence occurred. In fact, people store foodstuffs and stocks wane towards the harvest in August, September, and October. The Western and Northern regions exhibit basically the same patterns. These observations suggested a correlation between nutritional deficiencies and progression of AIDS as often occurs with other infections under some tropical agricultural systems. This study appeared to be the 1st study to document statistical significance of a possible seasonally recurring component to the diagnosis of clinical AIDS in a tropical country. Additional research is needed to determine whether this seasonal pattern is due to insufficient data quality or an association with malnutrition does indeed exist.

Civil war and the spread of AIDS in Central Africa.

Using ordinary least squares regression techniques this paper demonstrates, for the first time, that the classic association of war and disease substantially accounts for the presently observed geographical distribution of reported clinical AIDS cases in Uganda. Both the spread of HIV 1 infection in the 1980s, and the subsequent development of AIDS to its 1990 spatial pattern, are shown to be significantly and positively correlated with ethnic patterns of recruitment into the Ugandan National Liberation Army (UNLA) after the overthrow of Idi Amin some 10 years earlier in 1979. This correlation reflects the estimated mean incubation period of 8-10 years for HIV 1 and underlines the need for cognizance of historical factors which may have influenced current patterns of AIDS seen in Central Africa. The findings may have important implications for AIDS forecasting and control in African countries which have recently experienced war. The results are compared with parallel analyses of other HIV hypotheses advanced to account for the reported geographical distribution of AIDS in Uganda.

PIP: Statistical analyses suggest that military involvement has substantially affected the apparent geographical distribution of reported clinical AIDS cases in Uganda. Official estimates place the number of HIV infections in Uganda at 1 million, 6% of the country's population. Using statistical regression model, the authors test the viability of 3 hypotheses in explaining the geographical distribution of the epidemic: 1) the "truck town hypothesis," which proposes that the distribution of HIV and AIDS reflects the diffusion process in which major roads act as the main corridors of virus spread; 2) the "migrant labor hypothesis," which says that HIV spread from areas of labor demand in urban regions to areas of labor supply in rural regions through return migration; and 3) the "military involvement" hypothesis, which takes into account the historical link between servicemen, prostitutes, and the spread of STDs. The military involvement hypothesis proposes that the distribution of HIV is largely due to the 6-year civil war that began in Uganda in 1979, following the overthrow of Idi Amin. As the statistical regression shows, the truck town hypothesis and the migrant labor hypothesis fail to fully explain the district to district variability in AIDS incidence. The analysis, however, does reveal a highly significant positive relationship between the ethnic composition of the Ugandan National Liberation Army and the currently reported spatial pattern of clinical AIDS in the country, which makes sense, considering that the mean incubation period for HIV is estimated at 8-10 years. The authors note that these findings may serve to in forecasting and controlling the spread of AIDS in other African countries which have recently experience war.

Forecasting epidemic pathways for measles in Iceland: the use of simultaneous equation and logit models.

Six measles transmission chains between pairs and triplets of medical districts in Iceland are identified using monthly data for the 26 years from 1945 to 1970. The years studied are divided into two halves, a calibration period (1945-1957) and a forecast period (1958-1970). Some simultaneous equation models of the chains are developed and fitted using three-stage least squares. The resulting one month ahead forecasts are presented in terms of the expected case levels and as the probability of epidemics occurring. A single equation probability model using a logistic transformation is then formulated and compared with the simultaneous equation approach. The results obtained from the Icelandic study confirm in practice the advantages theoretically expected from setting up forecasting models containing geographically based chain transmission components.

Changes in the seasonal incidence of measles in Iceland, 1896--1974.

The changing seasonal patterns of reported measles cases in Iceland during this century are analysed. These changes are related to increased population mobility following the development of external and internal transport links, particularly since 1945. The forging of such links has resulted in a shift in the seasonal distribution of cases from one peculiar to the local social and economic conditions in Iceland to one broadly similar to that in other countries of northern temperate latitudes.