By employing the SIR model in this paper we sought to review studies of infectious disease during periods of economic crisis. Our primary interest and focus was on the experiences in middle and high income countries as those of poor countries raise other issues, some arising from their vulnerability in global markets, others from their very weak health infrastructure, and yet others from the particular burden of disease. Because of marked heterogeneity in the evidence, traditional meta-analytic methods to estimate the hazard of infectious disease spread cannot be applied. Rather, we aimed at identifying key pathways and evidence about the effects of crisis on infectious disease control, including risk of epidemics, emergence and excess deaths. To study the potential for emergence of infectious diseases, we sought to detect changes in the size of high-risk populations and degrees of population exposure to high-risk transmission environments that could be provoked by a crisis. For those additional risks attributable to a crisis, we sought to identify potential public health responses that could mitigate risks of infectious disease epidemics. ii. Search Strategy We first searched the literature for available systematic and narrative reviews that assessed the risks of infectious disease epidemics or emergence due to economic crisis. No systematic reviews were found. We next searched eight electronic databases for primary studies: Medline, Biosis, Cinahl, ECOnlit, Embase, Global Health, Scopus and Web of Science for - articles registered up to November 2010 (dating back to the initial entries of these enginges, e.g. Medline from 1950, Embase from 1947, etc.; see Table 1). Grey literature databases searched included on-line search engines (Google and Google Scholar) and databases of international organizations (World Health Organization, OECD, European Commission, World Bank, UNAIDS, ECDC and individual country public health institutes websites for European countries) (Table 2). The search terms included ‘‘infectious’’ and ‘‘communicable’’ while, to capture a broad range of effects associated with economic crises and their sequelae, we included the following search terms: economic crisis, fiscal crisis, financial crisis, economic recession, economic depression, economic conditions, economic insecurity, debt, macroeconomic conditions, unemployment, GDP, personnel downsizing, job loss, recession, banking crisis, and business cycle. The complete search strategy is detailed in the Web Annex. Given the complex definitional problems described above, a detailed initial discussion was held among the research team to achieve a shared understanding of the material that would be included, based on the categories of crises identified above. Inclusion criteria were defined broadly, so as to capture as broad a range of papers as possible initially, but only studies from developed, i.e. high, upper-middle and lower-middle-income nations, as defined by the World Bank [43], were included for the reasons noted above. Qualitative studies, analyses of individual financial markets, and non-English articles were excluded (see Web Annex). Additional exclusion criteria included articles that were qualitative case studies, that did not mention infectious or communicable diseases, and articles not pertaining to economic, financial or political crises (e.g. articles which discussed the impact of poverty on infectious disease transmission, but not in the context of an economic downturn or political crisis). iii. Screening of studies and data extraction The initial database was compiled from the electronic search and duplicates were removed. Two reviewers (MD and MS) screened these citations by title and abstract review. Rare cases of discordance (,0.5%) were resolved by consensus. Relevant Economic Crises and Infectious Diseases citations were organised according to whether they related two key parameters of the SIR model, transmission rate (S to I) or removal rate (I to R). A data entry form was developed and pilot tested in consultation with experts in the area of financial crisis and health. Relevant information from retrieved articles was extracted for a narrative synthesis by two reviewers and summarized in Tables 1 and 2. All selected studies were reviewed by both reviewers and an inter-rater agreement of 100% was obtained for the data. iv. Extracting and combining data We extracted data from each study on the following variables (Web Annex): countries; years examined; study design; measure(s) used to define economic or political crisis; health outcome(s); and key findings. Countries were categorised by level of development, as described above and health effects were categorised into adverse, beneficial, or none. Studies were then mapped onto the SIR model described above. Substantial differences in methods, data and context of existing studies render a statistical meta-analysis of the findings impossible and limit direct comparison between studies. Ideally, we would have extracted the ‘‘effect size’’ of the impact of – however defined – economic crisis for each study. However, in light of the absence of a common metric for assessing crises, the diversity in methodologies, and in outcome indicators, it was impossible to extract statistically determined effect size estimates that could be combined. For instance, a considerable number of studies merely described in broad terms how infectious disease prevalence or mortality evolved during a period of crisis. Other studies employed a more advanced statistical analysis, even though their ‘‘effect size’’ estimates cannot be considered as estimates of the true causal impact of the crisis. Thus, as we were unable to apply statistical criteria to the studies, our coding of their outcomes was ordinal, assessing whether the authors of a study identified an increase, decrease, or no change in infectious disease incidence, prevalence, and/or mortality rates as reported in the authors’ conclusions or the reported models and data. Results We identified 230 unique citations from all literature searches, and of these 37 publications were eligible for inclusion (Table 1). The majority (n = 28; 76%) were descriptive studies, as opposed to analytic studies. The 37 studies were conducted across 27 countries or regions: Out of the 37 studies a total of 30 studies identified adverse infectious disease outcomes, such as an incidence or mortality increases in association with economic crisis; the remaining 7 studies found reductions and/or the absence of a notable, significant effect. In some cases, however, there were also unexpected longer-term benefits of crises, which could not be measured in terms of health outcomes. For example, a rise in infectious disease in Mexico, caused by a deterioration in disease control systems, provided impetus for sweeping healthcare insurance reforms (Seguro Popular) [44]. After observing declining infectious disease mortality in the Great Depression, researchers began to develop ways of conceptualizing and measuring morbidity [45]. There has been speculation that patterns of infectious disease could be influenced by changes in travel and migration, although this is not supported by empirical evidence and the relatively small scale and complexity of any changes, given the now enormous magnitude of global travel, would make research on this issue difficult. Thus, where positive effects were identified, the links were often very tenuous, and the most that can be said is that a crisis can PLoS ONE | www.plosone.org 4 June 2011 | Volume 6 | Issue 6 | e20724