Every year, conflicts and natural disasters affect millions of people worldwide. However, the resources to assist those affected are perpetually insufficient. When emergencies strike, assistance organizations must decide where to prioritize their limited resources to reduce as much mortality and suffering as possible. At the start of their emergency response activities, organizations typically make three key decisions: 1) determine if they will respond 2) prioritize/triage the needs of the affected population; and 3) choose first response programs to implement. Many studies and authors note that these decisions are often based on insufficient evidence and personal judgement. This dissertation argues that we, as emergency responders, can do better. Epidemiologic methods can empower us to make better decisions based on better measurement, analysis, and evidence – improving outcomes for emergency affected persons, globally. This dissertation provides three examples of epidemiologic methods being used to inform critical emergency response decision points. Aim 1 addresses the first emergency response decision: prioritizing the most severe emergencies for response programing. Aim 2 focuses on the second emergency response decision: how can responders most accurately prioritize the needs of affected persons by using needs surveys, given the potential that needs vary by gender or age. Aim 3 examines the third decision: which response programs to implement, by summarizing the evidence base for the effectiveness of standard emergency programs. Methods In aim 1 I facilitated a panel of outbreak specialists from a leading emergency response organization to develop, test, and validate a new measure for the classification of outbreaks. I used classical scale development methods, including both qualitative and quantitative procedures. In aim 2 I used data from 12 emergency needs surveys to examine a common assumption that reported needs and experiences vary based on the gender and/or age of the respondent. I conducted both individual analyses of each study as well as a set of meta-analyses examining the prevalence differences found between gender and age sub-groups. In aim 3 I conducted a systematic scoping review of the evidence of what programs are effective in acute emergency settings. I searched six academic databases as well as eight sector-relevant grey literature databases -focusing on evidence for standard emergency interventions. Results In aim 1, a new outbreak classification measure was successfully developed based on inputs from the expert panel and a compiled dataset of indicators in global outbreak emergencies. The measure allows for the immediate (within two hours) classification of outbreaks. The expert panel participated in qualitative exercises where they developed a construct of ‘scale and severity of outbreak emergencies.’ This construct had four sub-dimensions, and a scale was developed to measure each sub-dimension, and then combined into a single measure. The content validity, criterion validity, construct validity, and reliability were examined for the measure. Criterion validity was based on a strong (0.87) correlation between the new outbreak measure and a ‘gold standard’ ranking of outbreak emergencies created by a group of emergency decision-makers (‘judges’). Similarly, construct validity was based on the measure performing as predicted when compared to measures of a similar/dissimilar construct, (convergent and divergent validity). The case for reliability was made using intraclass correlations between the new outbreak measure and the ‘gold standard’ measure (a robust result of a 0.87 using an ICC 3, 1), as well as comparing how well the outbreak measure worked alongside the conflict and natural disaster measures (another robust finding of 0.91 using an ICC 3, 1). In aim 2, I found that emergency affected persons of various gender or age groups very rarely differ in their responses to needs and experience questions in emergency surveys. When searching for differences in how gender or age groups report their households’ top three needs, meaningful differences in individual studies were found 6% of the time. When a meta-analysis of the same data was conducted across all needs questions in all 12 surveys, no meaningful differences were found between how either men or women report needs, or how different age groups report needs. Responses to questions about experiences (rather than needs) in emergencies were slightly more likely to vary by gender or age group. The meta-analysis of experience questions showed that across the 12 assessments differences in how gender or age groups experience emergencies were extremely rare (less than 4% of questions showed a meaningful summary prevalence difference). In aim 3 I identified 43 programs that are commonly implemented in acute emergency response. My scoping review searched for any studies that rigorously evaluated the impact of one or more of these programs. My search identified 4,005 unique studies; I screened them all for eligibility, resulting in only four studies that met all inclusion criteria. Thus 39 of the pre-identified, common emergency programs have no published evidence of their effectiveness in acute emergencies. The remaining four, each have one study in one context that demonstrates at least one positive effect of the program. Conclusion This dissertation provided evidence that epidemiologic methods can help solve problems, answer questions, and improve the allocation of resources in acute emergencies. While each aim focused on a unique decision point within acute emergency responses, they all contended with similar difficulties, such as incomplete and poor-quality data and a lack of shared definitions for what data points are relevant in decision-making. Yet in all three aims I found other similarities as well: there are relevant data available; and there are effective methods available that can answer many of our questions.

The genetic variation among extant life forms reflects the outcomes of evolution. The fodder of evolution – germline mutations – is shaped by the interplay among evolutionary forces – notably natural selection and random genetic drift. In turn, these forces leave footprints recorded in the genetic variation of extant life forms. Characterizing these footprints to understand how evolution works is at the heart of population genetics. To this end, massive datasets of genetic variation have opened new avenues of research, around how mutation rates evolve for instance, and reinvigorated long standing questions in population genetics, notably about the genetic basis of adaptation. In turn, theoretical models of evolution inform what kind of footprints we expect evolution to leave behind in such data. Two theoretical models that investigate open questions in population genetics are described in this thesis. In Chapter 1, I consider the evolution of germline mutation rates, particularly on short evolutionary timescales, and ask if recently observed variation in mutation rates among human lineages could be explained by evolution at genetic modifiers of mutation rates. Genetic modifiers of mutation rates are expected to evolve under purifying selection: mutations at modifiers that increase mutation rates (“mutator alleles”) should be selected against, because they increase the burden of deleterious mutations in individuals who carry them. The frequencies of mutator alleles are also affected by mutation, genetic drift, and demographic processes. We model the evolution of mutator alleles under the interplay of these forces and characterize the dynamics at mutation rate modifiers as a function of the efficacy of selection acting on them. We find that modifiers under intermediate selection have the greatest contribution to variation in mutation rates between distantly related populations, but only variation at strongly selected modifiers turns over fast enough to explain variation in mutation rates among human lineages. We also predict that strongly selected modifiers could be potentially identified in the contemporary datasets of human pedigrees used to study germline mutations. In Chapter 2, I consider a central and enduring question in evolutionary biology: whether adaptation typically arises from few large effect changes or from many small effect changes. Both sides are supported by ample evidence. Yet it is unclear how to translate this evidence into general answers about the genetic basis of adaptation, in part because different methodologies have different limitations and ask different questions. Theory may offer a way out of this quagmire or at least a start. To this end, we reframe the question in terms of traits and ask: how does the genetic basis of adaptation depend on the ecological and genetic attributes of a trait? To start answering this question, I model adaptation in a simple yet highly relevant setting. I consider a trait under stabilizing selection and assume the distribution of trait values in the population is initially at mutation-selection-drift-balance. I then characterize the adaptive response that is elicited by a sudden change in the environment. I find that the adaptive response, and notably the probability that adaptation arises from the fixation of large effect alleles, depends on the size of the environmental change and the genetic architecture of the trait. These attributes are measurable and can be directly related to the disparate evidence that we have about the genetic basis of adaptation. Thus, this kind of modeling may help translate such evidence into general conclusions about how traits evolve. My thesis work was interrupted by the global COVID-19 pandemic, and in response to this pandemic, governments around the world implemented shelter-in-place protocols. However, essential workers were exempt from these protocols, potentially decreasing their efficacy. In Chapter 3, we describe our epidemiological project, aimed at understanding the impact of essential workers on epidemic control. To this end, we model three different archetypes of essential workers under a reasonably realistic SEIR model of the COVID-19 pandemic. We find that the different social interactions that essential workers maintain qualitatively changes their personal risk of infection and the spread of the overall epidemic. These results highlight the utility of not considering essential workers as a monolithic group but instead distinguishing between the impact of different types of essential workers on epidemic control.

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An accurate understanding of a population’s risk perception is important, as risk perception can influence attitudes to new policies and recommended health behaviours. There is a lack of research on the possible impact that Swedish news media could have on the Swedish population’s risk perception of natural hazards. This thesis has aimed to investigate the relationship between newspaper coverage and risk perception of natural hazards by quantifying newspaper coverage and comparing it with survey data on perceived likelihood and impact of several hazards (floods, droughts, wildfires, epidemics, and climate change). Direct experience which in this thesis meant direct involvement with a hazard was shown to be the main cause of increased risk perception for floods, droughts and wildfire, while no significant impact of newspaper coverage could be found. Survey data and newspaper coverage did however suggest that there is a significant impact on epidemics risk perception. Risk perception of climate change was found to be the hazard most tied to direct experience, but it was also correlated with newspaper coverage. This means that there is a possibility of newspaper coverage impacting risk perception of climate change. Climate change was also found to be mentioned frequently in connection with the other hazards, this could reinforce the idea that climate change intensifies the other hazards and thus increases risk perception. / En korrekt förståelse för en befolknings riskuppfattning är viktig, eftersom riskuppfattning kan påverka attityder till nya policyer och rekommenderade hälsobeteenden. Det saknas forskning om den möjliga inverkan som svenska nyhetsmedier kan ha på den svenska befolkningens riskuppfattning av naturkatastrofer. Denna uppsats ämnar att undersöka förhållandet mellan tidningstäckning och risk uppfattning av naturkatastrofer genom att kvantifiera mängden artiklar som nämner olika naturkatastrofer och jämföra dem med undersökningsdata om upplevd sannolikhet för inverkan av flera naturkatastrofer (översvämningar, torka, bränder, epidemier och klimatförändringar) ämnar denna uppsats att undersöka förhållandet mellan tidningstäckning och risk uppfattning. Resultaten från den här undersökningen visar att direkta erfarenheter av översvämningar, torka och skogsbränder var den främsta orsaken till ökad riskuppfattning, medan ingen betydande inverkan av tidningsnyheter kunde hittas. Undersökningsdata och tidningstäckning tyder dock på att det finns en betydande inverkan på riskuppfattningen av epidemier. Klimatförändringar visade sig vara den risk som var mest knuten till erfarenhet men, korrelerade också med mängden tidningsnyheter. Detta innebär att det är möjligt för tidningsartiklar att påverka riskuppfattningen av klimatförändringar. Klimatförändringar nämndes också ofta i samband med de andra farorna, vilket kan ha förstärkt idén att klimatförändringar intensifierar de andra naturkatastroferna och därmed ökat riskuppfattningen.

<p>This thesis examines patterns in poliomyelitis mortality in Wentworth and York Counties of southern Ontario, Canada, from 1900 to 1937. This period marked polio’s shift from endemic to epidemic status. It was also a time of shifting social, cultural, demographic, and economic patterns. Contemporaries struggled to understand polio’s epidemiology, and even today, with the poliovirus on the verge of global eradication, models to explain its changing patterns and impact continue to be revised.</p> <p>This thesis uses both qualitative and quantitative data collected from a variety of archival sources, including death, birth, and marriage registrations, census records, and newspaper articles, among other records. This information was used to build a geodatabase which forms the basis for analyses of mortality patterns in relation to age and sex, illness duration, seasonality, nativity, birthplace, ethnicity, and religion. Further analyses included family size, birth order, socioeconomic status, and place of residence patterns.</p> <p>Examined in the context of Wentworth and York Counties in the early 20^th century, the results both reveal a local pattern to polio’s epidemic emergence and provide a means to test broader hypotheses regarding polio’s epidemiological patterns. Specifically, results from this study were compared to the expectations of the intensive-exposure and cross-sex transmission hypotheses proposed by Nielsen and colleagues. Among the most important contributions of this thesis are the results showing a pattern of change over the study period, with two distinct stages. Stage One (1910 to 1927) is characterized by an equal sex ratio and a median known family size of four. Stage Two (1928 to 1937) is characterized by excess male deaths and a median known family size of two. These results link polio mortality patterns to demographic and ecological shifts in the early 20^th century and confirm that there is still much to learn from the history of this disease.</p> / Doctor of Philosophy (PhD)

We study fast-slow versions of the SIR, SIRS and SIRWS epidemiological models, and of the SIRS epidemiological model on homogeneous graphs, obtained through the application of the moment closure method. The multiple time scale behavior is introduced to account for large differences between some of the rates of the epidemiological pathways. Our main purpose is to show that the fast-slow models, even though in nonstandard form, can be studied by means of Geometric Singular Perturbation Theory (GSPT). In particular, without using Lyapunov's method, we are able to not only analyze the stability of the endemic equilibria of the SIR and SIRS models, but also to show that in the remaining models limit cycles arise. We show that the proposed approach is particularly useful in more complicated (higher dimensional) models such as the SIRWS model and the SIRS on homogeneous graphs, for which we provide a detailed description of their dynamics by combining analytic and numerical techniques. In particular, for the latter we show that the model can give rise to periodic solutions, differently from the corresponding model based on homogeneous mixing.

范家偉. / 論文(博士)--香港中文大學歷史學部, 1997. / 附參考文獻. / 中英文摘要. / Available also through the Internet via Dissertations & theses @ Chinese University of Hong Kong. / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Fan Jiawei. / Lun wen (Bo shi)--Xianggang Zhong wen da xue li shi xue bu, 1997. / Fu can kao wen xian. / Zhong Ying wen zhai yao.

Thesis (PhD (Physics))--Stellenbosch University, 2009. / ENGLISH ABSTRACT: This dissertation investigates certain key aspects of mathematical modeling of HIV and TB epidemics in South Africa with particular emphasis on data from a single well-studied community. Data collected over a period of 15 years (1994 to 2009) in Masiphumelele, a township near Cape Town, South Africa are used to develop a community-level mathematical model of the local HIV-TB epidemic. The population is divided into six compartments and a system of di®erential equations is derived to describe the spread of the dual epidemic. Our numerical results suggest that increased access to antiretroviral therapy (ART) could decrease not only the HIV prevalence, but also the TB noti¯cation rate. We present a modeling framework for studying the statistical properties of °uctuations in models of any population of a similar size. Viewing the epidemic as a jump process, the method entails an expansion of a master equation in a small parameter; in this case in inverse powers of the square root of the population size. We derive two-time correlation functions to study the correlation between di®erent types of active TB events, and show how a temporal element could be added to the de¯nition of TB clusters, which are currently de¯ned solely by DNA type. We add age structure to the HIV-TB model in order to investigate the demographical impact of HIV-TB epidemics. Our analysis suggests that, contrary to general belief, HIV-positive cases are not making a substantial contribution to the spread of TB in Masiphumelele. We develop an age-structured model of the HIV-TB epidemic at a national level in order to study the potential impact of a proposed universal test and treat program for HIV on dual HIV-TB epidemics. Our simulations show that generalized ART could signi¯cantly reduce the TB noti¯cation rate and the TB-related mortality rate in the short term. The timescale of the impact of ART on HIV prevalence is likely to be longer. We study the potential impact of more conventional control measures against HIV. Guidance for possible future and/or additional interventions emerge naturally from the results. We advocate a reduction in intergenerational sex, based on our ¯nding that 1.5-2.5 standard deviation in the age di®erence between sexual partners is necessary to create and sustain a major HIV epidemic. A simulation framework is developed to help quantify variance in age-structured epidemic models. The expansion technique is generalized to derive a Fokker-Planck equation. Directions for future work, particularly in terms of developing methods to model °uctuations and validate mixing assumptions in epidemiological models, are identi¯ed. / AFRIKAANSE OPSOMMING: Hierdie proefskrif ondersoek aspekte van die wiskundige modelering van HIV en TB epi- demies in Suid Afrika en fokus ook op 'n spesi¯eke gemeenskap. Data wat oor 'n periode van 15 jaar ingesamel is (1994 tot 2009) in Masiphumelele, 'n woonbuurt naby Kaapstad, Suid Afrika word gebruik om 'n wiskundige model te skep wat HIV-TB in die gemeen- skap modeleer. Die populasie word in ses kompartemente verdeel en 'n stel di®erensiaal vergelykings word afgelei om die verspreiding van di¶e epidemies te ondersoek. Ons nu- meriese resultate toon aan dat verhoogde toegang tot antiretrovirale behandeling (ARB) die potensiaal het om HIV prevalensie die TB koers beduidend te laat daal. Ons ontwikkel 'n raamwerk waarmee die statistiese eienskappe van °uktuasies ondersoek kan word in enige populasie van dieselfde grootte. Die metode ontwikkel 'n meester vergelyking vir die on- derliggende geboorte-dood stogastiese proses en brei dit uit in terme van 'n klein parameter; in di¶e geval in inverse magte van die vierkantswortel van die populasie grootte. Die twee-tyd korrelasie funksies word afgelei, en word gebruik om die korrelasie tussen verskillende tipes van TB episodes te bestudeer, asook om te wys hoe 'n tydselement aan die de¯nisie van TB groeperings gegee kan word. Di¶e word tans slegs d.m.v DNA tipe geklassi¯seer. Ouderdom- struktuur word aan die model toegevoeg om die demogra¯ese impak van HIV-TB epidemies te bestudeer. Ons analise toon aan dat, anders as wat algemeen aanvaar word, maak HIV- positiewe gevalle nie 'n groot bydrae tot die verspreiding van TB in Masiphumelele nie. Ons ontwikkel 'n ouderdom-gestruktureerde model van HIV-TB op nasionale vlak en gebruik die model om die potensiÄele impak van 'n universele toets- en behandel strategie op die HIV-TB epidemies te ondersoek. Ons simulasies toon aan dat algemene ARB waarskynlik 'n groot impak op die TB aanmeldings koers asook die TB-verwante mortaliteits koers kan h^e binne 'n relatiewe kort tydperk. Die impak op HIV prevalensie sal eers oor 'n veel langer periode duidelik word. Ons ondersoek ook die moontlikheid van meer konvensionele beheermaa- treels. Ons ontmoedig tussengenerasie seksuale omgang, gegrond op ons bevinding dat 'n standaard afwyking van 1.5-2.5 in die ouderdoms verskil tussen seksuele vennote, nodig is om 'n HIV epidemie van stapel te stuur en te onderhou. Ons ontwikkel 'n simulasie raamwerk om variansie in ouderdomgestruktureerde modelle te benader. Die uitbreidingstegniek word veralgemeen om 'n Fokker-Planck vergelyking af te lei. Ons identi¯seer probleme in die on- twikkeling van metodes om interaksie patrone en °uktuasies te modeleer in epidemiologiese modelle as opgawe vir toekomstige werk.

published_or_final_version / abstract / Politics and Public Administration / Doctoral / Doctor of Philosophy

Doctor of Philosophy / Department of Electrical and Computer Engineering / Caterina Scoglio / Critical infrastructures are repeatedly attacked by external triggers causing tremendous amount of damages. Any infrastructure can be studied using the powerful theory of complex networks. A complex network is composed of extremely large number of different elements that exchange commodities providing significant services. The main functions of complex networks can be damaged by different types of attacks and failures that degrade the network performance. These attacks and failures are considered as disturbing dynamics, such as the spread of viruses in computer networks, the spread of epidemics in social networks, and the cascading failures in power grids. Depending on the network structure and the attack strength, every network differently suffers damages and performance degradation. Hence, quantifying the robustness of complex networks becomes an essential task. In this dissertation, new metrics are introduced to measure the robustness of technological and social networks with respect to the spread of epidemics, and the robustness of power grids with respect to cascading failures. First, we introduce a new metric called the Viral Conductance ($VC_{SIS}$) to assess the robustness of networks with respect to the spread of epidemics that are modeled through the susceptible/infected/susceptible ($SIS$) epidemic approach. In contrast to assessing the robustness of networks based on a classical metric, the epidemic threshold, the new metric integrates the fraction of infected nodes at steady state for all possible effective infection strengths. Through examples, $VC_{SIS}$ provides more insights about the robustness of networks than the epidemic threshold. In addition, both the paradoxical robustness of Barab\'si-Albert preferential attachment networks and the effect of the topology on the steady state infection are studied, to show the importance of quantifying the robustness of networks. Second, a new metric $VC_$ is introduced to assess the robustness of networks with respect to the spread of susceptible/infected/recovered ($SIR$) epidemics. To compute $VC_$, we propose a novel individual-based approach to model the spread of $SIR$ epidemics in networks, which captures the infection size for a given effective infection rate. Thus, $VC_$ quantitatively integrates the infection strength with the corresponding infection size. To optimize the $VC_$ metric, a new mitigation strategy is proposed, based on a temporary reduction of contacts in social networks. The social contact network is modeled as a weighted graph that describes the frequency of contacts among the individuals. Thus, we consider the spread of an epidemic as a dynamical system, and the total number of infection cases as the state of the system, while the weight reduction in the social network is the controller variable leading to slow/reduce the spread of epidemics. Using optimal control theory, the obtained solution represents an optimal adaptive weighted network defined over a finite time interval. Moreover, given the high complexity of the optimization problem, we propose two heuristics to find the near optimal solutions by reducing the contacts among the individuals in a decentralized way. Finally, the cascading failures that can take place in power grids and have recently caused several blackouts are studied. We propose a new metric to assess the robustness of the power grid with respect to the cascading failures. The power grid topology is modeled as a network, which consists of nodes and links representing power substations and transmission lines, respectively. We also propose an optimal islanding strategy to protect the power grid when a cascading failure event takes place in the grid. The robustness metrics are numerically evaluated using real and synthetic networks to quantify their robustness with respect to disturbing dynamics. We show that the proposed metrics outperform the classical metrics in quantifying the robustness of networks and the efficiency of the mitigation strategies. In summary, our work advances the network science field in assessing the robustness of complex networks with respect to various disturbing dynamics.