Acute hepatopancreatic necrosis disease (AHPND) is an emerging bacterial infection in shrimp that has been widespread across the major world shrimp producing countries since 2009. AHPND epizootics have resulted in a huge loss of global shrimp production, similar to that caused by white spot disease in the 1990’s. The epizootiological understanding of the spread of AHPND is still in its early stages, however, and most of the currently published research findings are based on experimental studies that may struggle to capture the potential for disease transmission at the country scale. The main aim of this research, therefore, is to develop epizootiological tools to study AHPND transmission between shrimp farming sites. Some tools used in this research have already been applied to shrimp epizoology, but others are used here for the first time to evaluate the spread of shrimp diseases. According to an epizootiological survey of AHPND in Thailand (Chapter 3), the first case of AHPND in the country was in eastern shrimp farms in January 2012. The disease was then transmitted to the south in December 2012. The results obtained from interviews, undertaken with 143 sample farms were stratified by three farm-scales (large, medium and small) and two locations (east and south). Both the southern location and large-scale farming were associated with a delay in AHPND onset compared with the eastern location and small- and medium-scale farming. The 24 risk factors (mostly related to farming management practices) for AHPND were investigated in a cross-sectional study (Chapter 3). This allowed the development of an AHPND decision tree for defining cases (diseased farms) and controls (non-diseased farms) because at the time of the study AHPND was a disease of unknown etiology. Results of univariate and unconditional logistic regression models indicated that two farming management practices related to the onset of AHPND. First, the absence of pond harrowing before shrimp stocking increased the risk of AHPND occurrence with an odds ratio () of 3.9 (95 % CI 1.3–12.6; P‑value = 0.01), whereas earthen ponds decreased the risk of AHPND with an of 0.25 (95 % CI 0.06–0.8; P‑value = 0.02). These findings imply that good farming management practices, such as pond-bottom harrowing, which are a common practice of shrimp farming in earthen ponds, may contribute to overcoming AHPND infection at farm level. For the purposes of disease surveillance and control, the structure of the live shrimp movement network within Thailand (LSMN) was modelled, which demonstrated the high potential for site-to-site disease spread (Chapter 4). Real network data was recorded over a 13-month period from March 2013 to March 2014 by the Thailand Department of Fisheries. After data validation, c. 74 400 repeated connections between 13 801 shrimp farming sites were retained. 77 % of the total connections were inter-province movements; the remaining connections were intra-province movements (23 %). The results demonstrated that the LSMN had properties that both aided and hindered disease spread (Chapter 4). For hindering transmission, the correlation between and degrees was weakly positive, i.e. it suggests that sites with a high risk of catching disease posed a low risk for transmitting the disease (assuming solely network spread), and the LSMN showed disassortative mixing, i.e. a low preference for connections joining sites with high degree linked to connections with high degree. However, there were low values for mean shortest path length and clustering. The latter characteristics tend to be associated with the potential for disease epidemics. Moreover, the LSMN displayed the power-law in both and degree distributions with the exponents 2.87 and 2.17, respectively. The presence of power-law distributions indicates that most sites in the LSMN have a small number of connections, while a few sites have large numbers of connections. These findings not only contribute to a better understanding of disease spread between sites, therefore, but also reveal the importance of targeted disease surveillance and control, due to the detection of scale-free properties in the LSMN. Chapter 5, therefore, examined the effectiveness of targeted disease surveillance and control in respect to reducing the potential size of epizootics in the LSMN. The study untilised network approaches to identify high-risk connections, whose removal from the network could reduce epizootics. Five disease-control algorithms were developed for the comparison: four of these algorithms were based on centrality measures to represent targeted approaches, with a non-targeted approach as a control. With the targeted approaches, technically admissible centrality measures were considered: the betweenness (the number of shortest paths that go through connections in a network), connection weight (the frequency of repeated connections between a site pair), eigenvector (considering the degree centralities of all neighbouring sites connected to a specified site), and subnet-crossing (prioritising connections that links two different subnetworks). The results showed that the estimated epizootic sizes were smaller when an optimal targeted approach was applied, compared with the random targeting of high-risk connections. This optimal targeted approach can be used to prioritise targets in the context of establishing disease surveillance and control programmes. With complex modes of disease transmission (i.e. long-distance transmission like via live shrimp movement, and local transmission), an compartmental, individual-based epizootic model was constructed for AHPND (Chapter 6). The modelling uncovered the seasonality of AHPND epizootics in Thailand, which were found likely to occur between April and August (during the hot and rainy seasons of Thailand). Based on two movement types, intra-province movements were a small proportion of connections, and they alone could cause a small AHPND epizootic. The main pathway for AHPND spread is therefore long-distance transmission and regulators need to increase the efficacy of testing for diseases in farmed shrimp before movements and improve the conduct of routine monitoring for diseases. The implementation of these biosecurity practices was modelled by changing the values of the long-distance transmission rate. The model demonstrated that high levels of biosecurity on live shrimp movements (1) led to a decrease in the potential size of epizootics in Thai shrimp farming. Moreover, the potential size of epizootics was also decreased when AHPND spread was modelled with a decreased value for the local transmission rate. Hence, not only did the model predict AHPND epizootic dynamics stochastically, but it also assessed biosecurity enhancement, allowing the design of effective prevention programmes. In brief, this thesis develops tools for the systematic epizootiological study of AHPND transmission in Thai shrimp farming and demonstrates that: (1) at farm level, current Thai shrimp farming should enhance biosecurity systems even in larger businesses, (2) at country level, targeted disease control strategies are required to establish disease surveillance and control measures. Although the epizootiological tools used here mainly evaluate the spread of AHPND in shrimp farming sites, they could be adapted to other infectious diseases or other farming sectors, such as the current spread of tilapia lake virus in Nile tilapia farms.

Infectious diseases attract a lot of mediatic, cultural and political attention. But are those diseases like Ebola, or ‘disease x’ actually what kills us? Since 1946, the WHO is the most authoritative figure in the fights against infectious disease outbreaks. So how does the WHO maintain this power and authority after tremendous budget cuts, competition for authority, and a shift to non-communicable disease epidemiology? This thesis uses a mixed-methods approach of quantitative analysis of ‘Disease Outbreak News’ reports, and qualitative analysis of key WHO literature, to develop the alternative narrative answering those questions. This thesis found that the WHO activities surrounding the collection and distribution of data create a political and institutional environment in which the WHO seems to be the only logical solution to prevent them. Additionally, the narrative put forth by the WHO prioritizes the ‘alert and response’ and operational capabilities of the organization to further expand authority in outbreak response. This study concludes that the WHO, through the collection and distribution of knowledge, and efforts to increase operational capability as seen through the Global Outbreak Alert and Response Network (GOARN), seeks to maintain normative authority and power as an international organization. / M.A. / Globalization of trade and travel has only increased the fear of infectious disease transmission. There is a great demand for a global health security system that is alert and capable. Based on this ‘threat’ the WHO justifies their role as global health leader. The Global Outbreak Alert and Response Network (GOARN) is the system that currently acts as the operational arm of the WHO, monitoring and coordinating response to infectious disease outbreaks globally. Despite the critical role of GOARN, its day-to-day endeavors remain unexplored by the public health field. This thesis analyzes how the WHO uses GOARN and its surveillance capabilities to collect and transform data as a method to maintain normative authority, and projects a powerful narrative as the leader of ‘alert and response’. In a competitive environment with limited financial resources, the WHO has adapted in terms of surveillance and operational capability to maintain its leadership and authority in the global public health field.

Traditional disease surveillance can be augmented with a wide variety of open sources, such as online news media, twitter, blogs, and web search records. Rapidly increasing volumes of these open sources are proving to be extremely valuable resources in helping analyze, detect, and forecast outbreaks of infectious diseases, especially new diseases or diseases spreading to new regions. However, these sources are in general unstructured (noisy) and construction of surveillance tools ranging from real-time disease outbreak monitoring to construction of epidemiological line lists involves considerable human supervision. Intelligent modeling of such sources using text mining methods such as, topic models, deep learning and dependency parsing can lead to automated generation of the mentioned surveillance tools. Moreover, real-time global availability of these open sources from web-based bio-surveillance systems, such as HealthMap and WHO Disease Outbreak News (DONs) can aid in development of generic tools which will be applicable to a wide range of diseases (rare, endemic and emerging) across different regions of the world. In this dissertation, we explore various methods of using internet news reports to develop generic surveillance tools which can supplement traditional surveillance systems and aid in early detection of outbreaks. We primarily investigate three major problems related to infectious disease surveillance as follows. (i) Can trends in online news reporting monitor and possibly estimate infectious disease outbreaks? We introduce approaches that use temporal topic models over HealthMap corpus for detecting rare and endemic disease topics as well as capturing temporal trends (seasonality, abrupt peaks) for each disease topic. The discovery of temporal topic trends is followed by time-series regression techniques to estimate future disease incidence. (ii) In the second problem, we seek to automate the creation of epidemiological line lists for emerging diseases from WHO DONs in a near real-time setting. For this purpose, we formulate Guided Epidemiological Line List (GELL), an approach that combines neural word embeddings with information extracted from dependency parse-trees at the sentence level to extract line list features. (iii) Finally, for the third problem, we aim to characterize diseases automatically from HealthMap corpus using a disease-specific word embedding model which were subsequently evaluated against human curated ones for accuracies. / Ph. D. / Infectious Disease Outbreaks are a threat to public health and economic stability of many countries. Traditional Disease Surveillance data released by organizations, such as CDC, ProMED is delayed and therefore, not reliable for real-time monitoring of infectious disease outbreaks. Recently, open source indicators, such as online news sources and social media sources (Twitter) have been shown to be effective in monitoring infectious disease outbreaks in real-time due to their volume, ease of availability and citizen participation. This dissertation focuses on developing multiple data analytic tools which perform automated analysis of online disease-related news articles with an aim to characterize infectious diseases and monitor their spatial and temporal progression in real-time. We show that temporal trends extracted from online news articles can be used to capture dynamics of multiple disease outbreaks, such as whooping cough outbreak in U.S. during summer of 2012, periodic outbreaks of H7N9 in China during 2013-2014 and emerging MERS outbreak in Saudi Arabia. However, online news reporting during infectious disease outbreaks is driven by interest and therefore, news coverage for certain diseases can be inconsistent over time leading to erroneous surveillance.

It is often important to detect an increase in the frequency of some event. Particular attention is given to medical events such as mortality or the incidence of a given disease, infection or birth defect. Observations are regularly taken in which either an incidence occurs or one does not. This dissertation contains the result of an investigation of prospective monitoring techniques in two distinct surveillance situations. In the first situation, the observations are assumed to be the results of independent Bernoulli trials. Some have suggested adapting the scan statistic to monitor such rates and detect a rate increase as soon as possible after it occurs. Other methods could be used in prospective surveillance, such as the Bernoulli cumulative sum (CUSUM) technique. Issues involved in selecting parameters for the scan statistic and CUSUM methods are discussed, and a method for computing the expected number of observations needed for the scan statistic method to signal a rate increase is given. A comparison of these methods shows that the Bernoulli CUSUM method tends to be more effective in detecting increases in the rate. In the second situation, the incidence information is available at multiple locations. In this case the individual sites often report a count of incidences on a regularly scheduled basis. It is assumed that the counts are Poisson random variables which are independent over time, but the counts at any given time are possibly correlated between regions. Multivariate techniques have been suggested for this situation, but many of these approaches have shortcomings which have been demonstrated in the quality control literature. In an attempt to remedy some of these shortcomings, a new control chart is recommended based on a multivariate exponentially weighted moving average. The average run-length performance of this chart is compared with that of the existing methods. / Ph. D.

In epidemiology it is often useful to monitor disease occurrences prospectively to determine the location and time when clusters of disease are forming. This aids in the prevention of illness and injury of the public and is the reason spatio-temporal disease surveillance methods are implemented. Care must be taken in the design and implementation of these types of surveillance methods so that the methods provide accurate information on the development of clusters. Here two spatio-temporal methods for prospective disease surveillance are considered. These include the local Knox monitoring method and a new wavelet-based prospective monitoring method. The local Knox surveillance method uses a cumulative sum (CUSUM) control chart for monitoring the local Knox statistic, which tests for space-time clustering each time there is an incoming observation. The detection of clusters of events occurring close together both temporally and spatially is important in finding outbreaks of disease within a specified geographic region. The local Knox surveillance method is based on the Knox statistic, which is often used in epidemiology to test for space-time clustering retrospectively. In this method, a local Knox statistic is developed for use with the CUSUM chart for prospective monitoring so that epidemics can be detected more quickly. The design of the CUSUM chart used in this method is considered by determining the in-control average run length (ARL) performance for different space and time closeness thresholds as well as for different control limit values. The effect of nonuniform population density and region shape on the in-control ARL is explained and some issues that should be considered when implementing this method are also discussed. In the wavelet-based prospective monitoring method, a surface of incidence counts is modeled over time in the geographical region of interest. This surface is modeled using Poisson regression where the regressors are wavelet functions from the Haar wavelet basis. The surface is estimated each time new incidence data is obtained using both past and current observations, weighing current observations more heavily. The flexibility of this method allows for the detection of changes in the incidence surface, increases in the overall mean incidence count, and clusters of disease occurrences within individual areas of the region, through the use of control charts. This method is also able to incorporate information on population size and other covariates as they change in the geographical region over time. The control charts developed for use in this method are evaluated based on their in-control and out-of-control ARL performance and recommendations on the most appropriate control chart to use for different monitoring scenarios is provided. / Ph. D.

Innovative ways to conduct disease surveillance are required to address the complexity of Ciguatera Fish Poisoning (CFP). Mixed methods were employed to explore CFP epidemiology and interdisciplinary approaches to its surveillance in the Turks and Caicos Islands (TCI). Quantitative analyses of cross-sectional data collected by the TCI’s National Epidemiology and Research Unit in 2010 demonstrated that a low percentage of residents reported lifetime histories of illness following fish consumption (3.9%). Furthermore, gender, age, island, and home remedy use were significantly associated with reported clinic visitation by ill individuals. Next, a multisectoral CFP surveillance model was conceptualized. A qualitative exploration of the model’s hypothetical integration into TCI’s health system revealed that several systemic and contextual factors could influence the future uptake of interdisciplinary CFP surveillance. Targeted interventions are recommended to improve national CFP surveillance and to facilitate the growth of interdisciplinary networks between stakeholders from TCI’s health, fisheries and environment sectors. / Canadian Institutes of Health Research, Ontario Veterinary College, University of Guelph, Ministry of Health and Human Resources of the Turks and Caicos

An enhanced notified enteric disease surveillance trial began on 1 July 2007 and continued until 30 June 2008. The aim of the trial was to measure the quality, timeliness and completeness of data collected and submitted by a regional Public Health Service (PHS) to the Institute of Environmental Science and Research Limited (ESR), via the national disease database (EpiSurv) for notified cases of enteric diseases. The trial evaluated two different methods of data collection: postal questionnaires and telephone interviews. Telephone interview techniques were used to improve the contact rate, timeliness and completeness of data gathered from all notified cases of campylobacteriosis in the Manawatu, Horowhenua and Tararua regions. The target set for the project was to achieve a 95% contact rate with 90% full completion of all EpiSurv data fields. For all notified cases of campylobacteriosis a 97% contact rate was achieved in a time frame of between zero to 20 days (three day median) and completeness of all the EpiSurv case report fields ranged between 96 – 100% in the final data. Prior to the commencement of the study, between 1 July 2004 to 30 June 2005, MidCentral PHS (MCPHS) made contact with around 58% of all notified cases of campylobacteriosis and 77% of all other notified enteric disease cases1 . A short pre-screen mail questionnaire, with reply-paid envelope, was sent to all notified cases of cryptosporidiosis, giardiasis, salmonellosis and yersiniosis in the MCPHS regions. EpiSurv case report fields were completed using information supplied in the returned questionnaires. Return rate, timeliness, and completeness were compared with the telephone interview group. Fifty three percent of cases we attempted to contact via mail questionnaire responded within two to 63 days (six day median) and completeness of all the EpiSurv case report fields ranged between 81 – 100%. In addition, we monitored the newly introduced ESR Early Aberration Reporting System (EARS) flags for increased levels of disease compared to historical disease rates, and assessed its usefulness as a tool to identify potential outbreaks in the region. While no outbreaks that had not already been identified by PHS staff were found by monitoring the EARS system, EARS has become an important tool in the MCPHS for comparing our rates of disease with bordering PHSs. EARS also provided a good quick reference tool for media enquiries and the graphs produced in EARS have been well utilised as visual aids for training and seminars presented during the trial period. The results of the surveillance trial initiatives were compared to the rest of New Zealand (NZ) over the same time frame and with a comparable, medium-sized, PHS. While the results of the telephone interviews from the MCPHS trial were close to the comparable PHS, they were significantly higher than for the rest of NZ. The postal questionnaires achieved a lower contact rate than the comparable PHS but similar to the rest of NZ. However, the quality of data gathered in the returned MCPHS postal questionnaire was significantly higher in most fields. Additional analysis was undertaken which indicated that those cases living in higher deprivation and rural areas were less likely to respond to a postal questionnaire. An over-representation of common enteric disease notifications from rural areas in the MCPHS was also highlighted by our research. This trial has shown the effectiveness of utilising telephone interviews and telemarketing techniques for gathering timely and complete data for human enteric disease surveillance within the MCPHS. It has also demonstrated that a short pre-screen questionnaire can be effective in collecting good quality data needed to complete the standard EpiSurv case report form.

An enhanced notified enteric disease surveillance trial began on 1 July 2007 and continued until 30 June 2008. The aim of the trial was to measure the quality, timeliness and completeness of data collected and submitted by a regional Public Health Service (PHS) to the Institute of Environmental Science and Research Limited (ESR), via the national disease database (EpiSurv) for notified cases of enteric diseases. The trial evaluated two different methods of data collection: postal questionnaires and telephone interviews. Telephone interview techniques were used to improve the contact rate, timeliness and completeness of data gathered from all notified cases of campylobacteriosis in the Manawatu, Horowhenua and Tararua regions. The target set for the project was to achieve a 95% contact rate with 90% full completion of all EpiSurv data fields. For all notified cases of campylobacteriosis a 97% contact rate was achieved in a time frame of between zero to 20 days (three day median) and completeness of all the EpiSurv case report fields ranged between 96 – 100% in the final data. Prior to the commencement of the study, between 1 July 2004 to 30 June 2005, MidCentral PHS (MCPHS) made contact with around 58% of all notified cases of campylobacteriosis and 77% of all other notified enteric disease cases1 . A short pre-screen mail questionnaire, with reply-paid envelope, was sent to all notified cases of cryptosporidiosis, giardiasis, salmonellosis and yersiniosis in the MCPHS regions. EpiSurv case report fields were completed using information supplied in the returned questionnaires. Return rate, timeliness, and completeness were compared with the telephone interview group. Fifty three percent of cases we attempted to contact via mail questionnaire responded within two to 63 days (six day median) and completeness of all the EpiSurv case report fields ranged between 81 – 100%. In addition, we monitored the newly introduced ESR Early Aberration Reporting System (EARS) flags for increased levels of disease compared to historical disease rates, and assessed its usefulness as a tool to identify potential outbreaks in the region. While no outbreaks that had not already been identified by PHS staff were found by monitoring the EARS system, EARS has become an important tool in the MCPHS for comparing our rates of disease with bordering PHSs. EARS also provided a good quick reference tool for media enquiries and the graphs produced in EARS have been well utilised as visual aids for training and seminars presented during the trial period. The results of the surveillance trial initiatives were compared to the rest of New Zealand (NZ) over the same time frame and with a comparable, medium-sized, PHS. While the results of the telephone interviews from the MCPHS trial were close to the comparable PHS, they were significantly higher than for the rest of NZ. The postal questionnaires achieved a lower contact rate than the comparable PHS but similar to the rest of NZ. However, the quality of data gathered in the returned MCPHS postal questionnaire was significantly higher in most fields. Additional analysis was undertaken which indicated that those cases living in higher deprivation and rural areas were less likely to respond to a postal questionnaire. An over-representation of common enteric disease notifications from rural areas in the MCPHS was also highlighted by our research. This trial has shown the effectiveness of utilising telephone interviews and telemarketing techniques for gathering timely and complete data for human enteric disease surveillance within the MCPHS. It has also demonstrated that a short pre-screen questionnaire can be effective in collecting good quality data needed to complete the standard EpiSurv case report form.

An enhanced notified enteric disease surveillance trial began on 1 July 2007 and continued until 30 June 2008. The aim of the trial was to measure the quality, timeliness and completeness of data collected and submitted by a regional Public Health Service (PHS) to the Institute of Environmental Science and Research Limited (ESR), via the national disease database (EpiSurv) for notified cases of enteric diseases. The trial evaluated two different methods of data collection: postal questionnaires and telephone interviews. Telephone interview techniques were used to improve the contact rate, timeliness and completeness of data gathered from all notified cases of campylobacteriosis in the Manawatu, Horowhenua and Tararua regions. The target set for the project was to achieve a 95% contact rate with 90% full completion of all EpiSurv data fields. For all notified cases of campylobacteriosis a 97% contact rate was achieved in a time frame of between zero to 20 days (three day median) and completeness of all the EpiSurv case report fields ranged between 96 – 100% in the final data. Prior to the commencement of the study, between 1 July 2004 to 30 June 2005, MidCentral PHS (MCPHS) made contact with around 58% of all notified cases of campylobacteriosis and 77% of all other notified enteric disease cases1 . A short pre-screen mail questionnaire, with reply-paid envelope, was sent to all notified cases of cryptosporidiosis, giardiasis, salmonellosis and yersiniosis in the MCPHS regions. EpiSurv case report fields were completed using information supplied in the returned questionnaires. Return rate, timeliness, and completeness were compared with the telephone interview group. Fifty three percent of cases we attempted to contact via mail questionnaire responded within two to 63 days (six day median) and completeness of all the EpiSurv case report fields ranged between 81 – 100%. In addition, we monitored the newly introduced ESR Early Aberration Reporting System (EARS) flags for increased levels of disease compared to historical disease rates, and assessed its usefulness as a tool to identify potential outbreaks in the region. While no outbreaks that had not already been identified by PHS staff were found by monitoring the EARS system, EARS has become an important tool in the MCPHS for comparing our rates of disease with bordering PHSs. EARS also provided a good quick reference tool for media enquiries and the graphs produced in EARS have been well utilised as visual aids for training and seminars presented during the trial period. The results of the surveillance trial initiatives were compared to the rest of New Zealand (NZ) over the same time frame and with a comparable, medium-sized, PHS. While the results of the telephone interviews from the MCPHS trial were close to the comparable PHS, they were significantly higher than for the rest of NZ. The postal questionnaires achieved a lower contact rate than the comparable PHS but similar to the rest of NZ. However, the quality of data gathered in the returned MCPHS postal questionnaire was significantly higher in most fields. Additional analysis was undertaken which indicated that those cases living in higher deprivation and rural areas were less likely to respond to a postal questionnaire. An over-representation of common enteric disease notifications from rural areas in the MCPHS was also highlighted by our research. This trial has shown the effectiveness of utilising telephone interviews and telemarketing techniques for gathering timely and complete data for human enteric disease surveillance within the MCPHS. It has also demonstrated that a short pre-screen questionnaire can be effective in collecting good quality data needed to complete the standard EpiSurv case report form.

The Innovative Medicines Initiative Accelerated Development of VAccine beNefit-risk Collaboration in Europe (IMI ADVANCE) project aims to develop a framework for best practice methods on integrated rapid benefit/risk monitoring of vaccines in the European Union (EU). Burden of disease is one of the measures considered when estimating vaccine benefits. This study explores the use of notifiable infectious disease surveillance data for this purpose by estimating burden of invasive meningococcal disease in the EU/European Economic Area (EEA). We use the Burden of Communicable Diseases in Europe toolkit for computing disability-adjusted life years from incidence-based data retrieved from the European Surveillance System (TESSy) held at the European Centre for Disease Prevention and Control. Invasive meningococcal is a common cause of meningitis and septicaemia, with high case-fatality (~10%) and sequelae. We found that the median annual burden of invasive meningococcal disease in the EU/EEA, 2011-2015, was 3.87 DALYs per 100 000 total population (95% UI: 3.79-3.95). Children below one year of age and children below five years of age were at greatest risk of invasive meningococcal disease serogroup B with 89.15 DALYs per 100 000 stratum specific population (95% UI: 83.11-95.02) and 22.57 DALYs per 100 000 stratum specific population (95% UI: 21.03-24.12), respectively. We found that the distribution of burden of invasive meningococcal disease serogroup B differs widely between countries in the EU/EEA and consequently confirm that national assessment of the new infant meningococcal B vaccine is highly relevant.