Geospatial investigations in Colombia reveal variations in the distribution of mood and psychotic disorders

BACKGROUND

Geographical variations in mood and psychotic disorders have been found in upper-income countries. We looked for geographic variation in these disorders in Colombia, a middle-income country. We analyzed electronic health records from the Clínica San Juan de Dios Manizales (CSJDM), which provides comprehensive mental healthcare for the one million inhabitants of Caldas.

METHODS

We constructed a friction surface map of Caldas and used it to calculate the travel-time to the CSJDM for 16,295 patients who had received an initial diagnosis of mood or psychotic disorder. Using a zero-inflated negative binomial regression model, we determined the relationship between travel-time and incidence, stratified by disease severity. We employed spatial scan statistics to look for patient clusters.

RESULTS

We show that travel-times (for driving) to the CSJDM are less than 1 h for ~50% of the population and more than 4 h for ~10%. We find a distance-decay relationship for outpatients, but not for inpatients: for every hour increase in travel-time, the number of expected outpatient cases decreases by 20% (RR = 0.80, 95% confidence interval [0.71, 0.89], p = 5.67E-05). We find nine clusters/hotspots of inpatients.

CONCLUSIONS

Our results reveal inequities in access to healthcare: many individuals requiring only outpatient treatment may live too far from the CSJDM to access healthcare. Targeting of resources to comprehensively identify severely ill individuals living in the observed hotspots could further address treatment inequities and enable investigations to determine factors generating these hotspots.

The role of migration networks in the development of Botswana's generalized HIV epidemic

The majority of people with HIV live in sub-Saharan Africa, where epidemics are generalized. For these epidemics to develop, populations need to be mobile. However, the role of population-level mobility in the development of generalized HIV epidemics has not been studied. Here we do so by studying historical migration data from Botswana, which has one of the most severe generalized HIV epidemics worldwide; HIV prevalence was 21% in 2021. The country reported its first AIDS case in 1985 when it began to rapidly urbanize. We hypothesize that, during the development of Botswana's epidemic, the population was extremely mobile and the country was highly connected by substantial migratory flows. We test this mobility hypothesis by conducting a network analysis using a historical time series (1981-2011) of micro-census data from Botswana. Our results support our hypothesis. We found complex migration networks with very high rates of rural-to-urban, and urban-to-rural, migration: 10% of the population moved annually. Mining towns (where AIDS cases were first reported, and risk behavior was high) were important in-flow and out-flow migration hubs, suggesting that they functioned as 'core groups' for HIV transmission and dissemination. Migration networks could have dispersed HIV throughout Botswana and generated the current hyperendemic epidemic.

Population mobility and the development of Botswana's generalized HIV epidemic: a network analysis

The majority of people with HIV live in sub-Saharan Africa, where HIV epidemics are generalized. For these epidemics to develop, populations need to be mobile. However, population-level mobility has not yet been studied in the context of the development of generalized HIV epidemics. Here we do so by studying historical migration data from Botswana which has one of the most severe generalized HIV epidemics worldwide; in 2021, HIV prevalence was 21%. The country reported its first AIDS case in 1985 when it began to rapidly urbanize. We hypothesize that, during the development of Botswana's epidemic, the population was highly mobile and there were substantial urban-to-rural and rural-to-urban migratory flows. We test this hypothesis by conducting a network analysis using a historical time series (1981 to 2011) of micro-census data from Botswana. We found 10% of the population moved their residency annually, complex migration networks connected urban with rural areas, and there were very high rates of rural-to-urban migration. Notably, we also found mining towns were both important in-flow and out-flow migration hubs; consequently, there was a very high turnover of residents in towns. Our results support our hypothesis, and together, provide one explanation for the development of Botswana's generalized epidemic.

Lack of ownership of mobile phones could hinder the rollout of mHealth interventions in Africa

Mobile Health interventions, which require ownership of mobile phones, are being investigated throughout Africa. We estimate the percentage of individuals who own mobile phones in 33 African countries, identify a relationship between ownership and proximity to a health clinic (HC), and quantify inequities in ownership. We investigate basic mobile phone (BPs) and smartphones (SPs): SPs can connect to the internet, BPs cannot. We use nationally representative data collected in 2017-2018 from 44,224 individuals in Round 7 of the Afrobarometer surveys. We use Bayesian Multilevel Logistic regression models for our analyses. We find 82% of individuals in the 33 countries own mobile phones: 42% BPs, 40% SPs. Individuals who live close to an HC have higher odds of ownership than those who do not (adjusted odds ratio [aOR]: 1.31, Bayesian 95% Highest Posterior Density [HPD] region: 1.24-1.39). Men, compared with women, have over twice the odds of ownership (aOR: 2.37, 95% HPD region: 1.96-2.84). Urban residents, compared with rural residents, have almost three times the odds (aOR: 2.66, 95% HPD region: 2.22-3.18) and, amongst mobile phone owners, nearly three times the odds of owning an SP (aOR: 2.67, 95% HPD region: 2.33-3.10). Ownership increases with age, peaks in 26-40 year olds, then decreases. Individuals under 30 are more likely to own an SP than a BP, older individuals more likely to own a BP than an SP. Probability of ownership decreases with the Lived Poverty Index; however, some of the poorest individuals own SPs. If the digital devices needed for mHealth interventions are not equally available within the population (which we have found is the current situation), rolling out mHealth interventions in Africa is likely to propagate already existing inequities in access to healthcare.

Predicting the transmission of SARS-CoV-2 in Africa: the case of Namibia

SARS-CoV-2 transmission models have been fairly inaccurate in their predictions for Africa. Here, based on an analysis of surveillance data from Namibia, we conclude that it is necessary to include spatial demography, and travel, in SARS-CoV-2 transmission models in order to make more accurate predictions for COVID-19 epidemics in Africa.

The potential impact of country-level migration networks on HIV epidemics in sub-Saharan Africa: the case of Botswana

Generalised HIV epidemics in sub-Saharan Africa show substantial geographical variation in prevalence, which is considered when designing epidemic control strategies. We hypothesise that the migratory behaviour of the general population of countries in sub-Saharan Africa could have a substantial effect on HIV epidemics and challenge the elimination effort. To test this hypothesis, we used census data from 2017 to identify, construct, and visualise the migration network of the population of Botswana, which has one of the most severe HIV epidemics worldwide. We found that, over 12 months, approximately 14% of the population moved their residency from one district to another. Four types of migration occurred: urban-to-urban, rural-to-urban, urban-to-rural, and rural-to-rural. Migration is leading to a marked geographical redistribution of the population, causing high rates of population turnover in some areas, and further concentrating the population in urban areas. The migration network could potentially be having a substantial effect on the HIV epidemic of Botswana: changing the location of high-transmission areas, generating cross-country transmission corridors, creating source-sink dynamics, and undermining control strategies. Large-scale migration networks could present a considerable challenge to eliminating HIV in Botswana and in other countries in sub-Saharan Africa, and should be considered when designing epidemic control strategies.

Using mobile phone data to reveal risk flow networks underlying the HIV epidemic in Namibia

Twenty-six million people are living with HIV in sub-Saharan Africa; epidemics are widely dispersed, due to high levels of mobility. However, global elimination strategies do not consider mobility. We use Call Detail Records from 9 billion calls/texts to model mobility in Namibia; we quantify the epidemic-level impact by using a mathematical framework based on spatial networks. We find complex networks of risk flows dispersed risk countrywide: increasing the risk of acquiring HIV in some areas, decreasing it in others. Overall, 40% of risk was mobility-driven. Networks contained multiple risk hubs. All constituencies (administrative units) imported and exported risk, to varying degrees. A few exported very high levels of risk: their residents infected many residents of other constituencies. Notably, prevalence in the constituency exporting the most risk was below average. Large-scale networks of mobility-driven risk flows underlie generalized HIV epidemics in sub-Saharan Africa. In order to eliminate HIV, it is likely to become increasingly important to implement innovative control strategies that focus on disrupting risk flows.

HIV transmission and source-sink dynamics in sub-Saharan Africa

Multiple phylogenetic studies of HIV in sub-Saharan Africa have shown that mobility-driven transmission frequently occurs: many communities export and import strains. Mobility-driven transmission can result in source-sink dynamics: one community can sustain a micro-epidemic in another community in which transmission is too low to be self-sustaining. In epidemiology, the basic reproduction number (R₀) is used to specify the sustainability threshold. R₀ represents the average number of secondary infections generated by one infected individual in a community in which everyone is susceptible. If R₀ is greater than 1, transmission is high enough to sustain an epidemic; if R₀ is less than 1, it is not. Here, we discuss the conditions that are needed (in terms of R₀) for source-sink transmission dynamics to occur in generalised HIV epidemics in sub-Saharan Africa, present an example of where these conditions could occur (ie, Namibia), and discuss the necessity of considering mobility-driven transmission when designing control strategies. Additionally, we discuss the need for a new generation of HIV transmission models that are more realistic than the current models. The new models should reflect not only geographical variation in epidemiology and demography, but also the spatial-temporal complexity of population-level movement patterns.

A modeling study of the Danish HIV epidemic in men who have sex with men: travel, pre-exposure prophylaxis and elimination

UNAIDS has identified the Danish HIV epidemic in men who have sex with men (MSM) as a priority for elimination. Incidence is close to the elimination threshold of one new infection per year per 1,000 individuals. However, surveillance data show that HIV strains are being imported into Denmark, mainly due to travel. We use a transmission model to predict (from 2018 to 2030) the impact of pre-exposure prophylaxis (PrEP) on incidence. Our model reflects the current epidemic and diagnosis rates in the Danish MSM community. We conduct a sensitivity analysis based on 20,000 simulations, and assume that PrEP coverage could range from zero to 50% and diagnosis rates increase up to three-fold. We predict that incidence will fall below the elimination threshold, even without the introduction of PrEP, reaching 0.87 (median, 95% Confidence Interval: 0.65-1.23) new infections per 1,000 MSM by 2030. PrEP could reduce incidence to well below the threshold, if it results in a significant increase in diagnosis rates and reduces the number of infections occurring abroad. The Danish Medicine Agency and Danish Health Authority have recommended introducing PrEP. Our study provides strong support for this recommendation, and shows the importance of Danish MSM using PrEP when abroad.

Geographic variation in sexual behavior can explain geospatial heterogeneity in the severity of the HIV epidemic in Malawi

BACKGROUND

In sub-Saharan Africa, where ~ 25 million individuals are infected with HIV and transmission is predominantly heterosexual, there is substantial geographic variation in the severity of epidemics. This variation has yet to be explained. Here, we propose that it is due to geographic variation in the size of the high-risk group (HRG): the group with a high number of sex partners. We test our hypothesis by conducting a geospatial analysis of data from Malawi, where ~ 13% of women and ~ 8% of men are infected with HIV.

METHODS

We used georeferenced HIV testing and behavioral data from ~ 14,000 participants of a nationally representative population-level survey: the 2010 Malawi Demographic and Health Survey (MDHS). We constructed gender-stratified epidemic surface prevalence (ESP) maps by spatially smoothing and interpolating the HIV testing data. We used the behavioral data to construct gender-stratified risk maps that reveal geographic variation in the size of the HRG. We tested our hypothesis by fitting gender-stratified spatial error regression (SER) models to the MDHS data.

RESULTS

The ESP maps show considerable geographic variation in prevalence: 1-29% (women), 1-20% (men). Risk maps reveal substantial geographic variation in the size of the HRG: 0-40% (women), 16-58% (men). Prevalence and the size of the HRG are highest in urban centers. However, the majority of HIV-infected individuals (~75% of women, ~ 80% of men) live in rural areas, as does most of the HRG (~ 80% of women, ~ 85% of men). We identify a significant (P < 0.001) geospatial relationship linking the size of the HRG with prevalence: the greater the size, the higher the prevalence. SER models show HIV prevalence in women is expected to exceed the national average in districts where > 20% of women are in the HRG. Most importantly, the SER models show that geographic variation in the size of the HRG can explain a substantial proportion (73% for women, 67% for men) of the geographic variation in epidemic severity.

CONCLUSIONS

Taken together, our results provide substantial support for our hypothesis. They provide a potential mechanistic explanation for the geographic variation in the severity of the HIV epidemic in Malawi and, potentially, in other countries in sub-Saharan Africa.

Response to comment on "Using geospatial mapping to design HIV elimination strategies for sub-Saharan Africa"

Detailed geospatial mapping of a generalized HIV epidemic in sub-Saharan Africa shows that implementing the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 strategy could potentially exacerbate urban-rural health care disparities.

Using geospatial mapping to design HIV elimination strategies for sub-Saharan Africa

Treatment as prevention (TasP) has been proposed by the World Health Organization and the Joint United Nations Programme on HIV/AIDS (UNAIDS) as a global strategy for eliminating HIV. The rationale is that treating individuals reduces their infectivity. We present a geostatistical framework for designing TasP-based HIV elimination strategies in sub-Saharan Africa. We focused on Lesotho, where ~25% of the population is infected. We constructed a density of infection map by gridding high-resolution demographic data and spatially smoothing georeferenced HIV testing data. The map revealed the countrywide geographic dispersion pattern of HIV-infected individuals. We found that ~20% of the HIV-infected population lives in urban areas and that almost all rural communities have at least one HIV-infected individual. We used the map to design an optimal elimination strategy and identified which communities should use TasP. This strategy minimized the area that needed to be covered to find and treat HIV-infected individuals. We show that UNAIDS's elimination strategy would not be feasible in Lesotho because it would require deploying treatment in areas where there are ~4 infected individuals/km2 Our results show that the spatial dispersion of Lesotho's population hinders, and may even prevent, the elimination of HIV.

Testing the hypothesis that treatment can eliminate HIV: a nationwide, population-based study of the Danish HIV epidemic in men who have sex with men

BACKGROUND

Worldwide, approximately 35 million individuals are infected with HIV; about 25 million of these live in sub-Saharan Africa. WHO proposes using treatment as prevention (TasP) to eliminate HIV. Treatment suppresses viral load, decreasing the probability an individual transmits HIV. The elimination threshold is one new HIV infection per 1000 individuals. Here, we test the hypothesis that TasP can substantially reduce epidemics and eliminate HIV. We estimate the impact of TasP, between 1996 and 2013, on the Danish HIV epidemic in men who have sex with men (MSM), an epidemic UNAIDS has identified as a priority for elimination.

METHODS

We use a CD4-staged Bayesian back-calculation approach to estimate incidence, and the hidden epidemic (the number of HIV-infected undiagnosed MSM). To develop the back-calculation model, we use data from an ongoing nationwide population-based study: the Danish HIV Cohort Study.

FINDINGS

Incidence, and the hidden epidemic, decreased substantially after treatment was introduced in 1996. By 2013, incidence was close to the elimination threshold: 1·4 (median, 95% Bayesian credible interval [BCI] 0·4-2·1) new HIV infections per 1000 MSM and there were only 617 (264-858) undiagnosed MSM. Decreasing incidence and increasing treatment coverage were highly correlated; a treatment threshold effect was apparent.

INTERPRETATION

Our study is the first to show that TasP can substantially reduce a country's HIV epidemic, and bring it close to elimination. However, we have shown the effectiveness of TasP under optimal conditions: very high treatment coverage, and exceptionally high (98%) viral suppression rate. Unless these extremely challenging conditions can be met in sub-Saharan Africa, the WHO's global elimination strategy is unlikely to succeed.

FUNDING

National Institute of Allergy and Infectious Diseases.

Mapping divided households and residency changes: the effect of couple separation on sexual behavior and risk of HIV infection

Using census data we identify geographic patterns in residency changes in Lesotho over a decade. Using kriging to spatially interpolate data from 8,510 households we identify regions where households have members temporarily living away from home (divided households). Further, using a multivariate analysis and data from 2,026 couples we determine whether a partners’ absence increases the likelihood of having extramarital partners and/or risk of HIV infection. Approximately 40% of individuals moved between 2001 and 2011; mainly to, and within, urbanized regions. Many households are divided: ~40% have members elsewhere in Lesotho, ~30% in South Africa (SA). Geographic patterns are apparent; they differ based on where the household member is living. Many couples were temporarily separated: ~50% of wives, ~20% of husbands. Separation was not a risk factor for HIV. Only men were more likely to have extramarital partners if their spouse was away: ~1.5 times if in Lesotho, ~3 times if in SA. The high degree of geographic mixing necessitates synchronizing interventions within Lesotho, and with SA, to successfully reduce transmission. It will be challenging to reduce concurrency in men with wives away from home. Our results are generalizable to other sub-Saharan countries where residency changes are common.

Using geospatial modelling to optimize the rollout of antiretroviral-based pre-exposure HIV interventions in Sub-Saharan Africa

Antiretroviral-based pre-exposure HIV interventions may soon be rolled out in resource-constrained Sub-Saharan African countries, but rollout plans have yet to be designed. Here we use geospatial modeling and optimization techniques to compare two rollout plans for ARV-based microbicides in South Africa: a utilitarian plan that minimizes incidence by using geographic targeting, and an egalitarian plan that maximizes geographic equity in access to interventions. We find significant geographic variation in the efficiency of interventions in reducing HIV transmission, and that efficiency increases disproportionately with increasing incidence. The utilitarian plan would result in considerable geographic inequity in access to interventions, but (by exploiting geographic variation in incidence) could prevent ~40% more infections than the egalitarian plan. Our results show that the geographic resource allocation decisions made at the beginning of a rollout, and the location where the rollout is initiated, will be crucial in determining the success of interventions in reducing HIV epidemics.

Increasing survival time decreases the cost-effectiveness of using "test & treat'' to eliminate HIV epidemics

Treating HIV-infected individuals reduces their viral load, consequently increasing their survival time and decreasing their infectivity. It has been proposed that universal testing and treatment (i.e., universal "test & treat'') could lead to HIV elimination and would be extremely cost-effective. It is now being debated whether to use a universal "test & treat'' approach in the "real-world'' as a prevention strategy to control HIV epidemics. However current modeling predictions of the impact, and cost-effectiveness, of universal `"est & treat'' strategies are based on an unrealistically short survival time for treated individuals. Here we use mathematical modeling and a longer, more realistic, survival time. We model the potential impact of a universal "test & treat'' strategy in South Africa. Our results show that increasing the length of the survival time on treatment, although beneficial to individuals, reduces the probability of eliminating HIV and decreases the cost-effectiveness of using universal "test & treat'' strategies. Therefore our results show that individual-level benefits and public health benefits will conflict when using "test &treat'' strategies to reduce HIV transmission.

Universal access to HIV treatment versus universal 'test and treat': transmission, drug resistance & treatment costs

In South Africa (SA) universal access to treatment for HIV-infected individuals in need has yet to be achieved. Currently ∼1 million receive treatment, but an additional 1.6 million are in need. It is being debated whether to use a universal ‘test and treat’ (T&T) strategy to try to eliminate HIV in SA; treatment reduces infectivity and hence transmission. Under a T&T strategy all HIV-infected individuals would receive treatment whether in need or not. This would require treating 5 million individuals almost immediately and providing treatment for several decades. We use a validated mathematical model to predict impact and costs of: (i) a universal T&T strategy and (ii) achieving universal access to treatment. Using modeling the WHO has predicted a universal T&T strategy in SA would eliminate HIV within a decade, and (after 40 years) cost ∼$10 billion less than achieving universal access. In contrast, we predict a universal T&T strategy in SA could eliminate HIV, but take 40 years and cost ∼$12 billion more than achieving universal access. We determine the difference in predictions is because the WHO has under-estimated survival time on treatment and ignored the risk of resistance. We predict, after 20 years, ∼2 million individuals would need second-line regimens if a universal T&T strategy is implemented versus ∼1.5 million if universal access is achieved. Costs need to be realistically estimated and multiple evaluation criteria used to compare ‘treatment as prevention’ with other prevention strategies. Before implementing a universal T&T strategy, which may not be sustainable, we recommend striving to achieve universal access to treatment as quickly as possible. We predict achieving universal access to treatment would be a very effective ‘treatment as prevention’ approach and bring the HIV epidemic in SA close to elimination, preventing ∼4 million infections after 20 years and ∼11 million after 40 years.

Modeling dynamic interactions between pre-exposure prophylaxis interventions & treatment programs: predicting HIV transmission & resistance

Clinical trials have recently demonstrated the effectiveness of Pre-Exposure Prophylaxis (PrEP) in preventing HIV infection. Consequently, PrEP may soon be used for epidemic control. We model the dynamic interactions that will occur between treatment programs and potential PrEP interventions in resource-constrained countries. We determine the consequences for HIV transmission and drug resistance. We use response hypersurface modeling to predict the effect of PrEP on decreasing transmission as a function of effectiveness, adherence and coverage. We predict PrEP will increase need for second-line therapies (SLT) for treatment-naïve individuals, but could significantly decrease need for SLT for treatment-experienced individuals. If the rollout of PrEP is carefully planned it could increase the sustainability of treatment programs. If not, need for SLT could increase and the sustainability of treatment programs could be compromised. Our results show the optimal strategy for rolling out PrEP in resource-constrained countries is to begin around the "worst" treatment programs.

HIV, transmitted drug resistance, and the paradox of preexposure prophylaxis

The administration of antiretrovirals before HIV exposure to prevent infection (i.e., preexposure prophylaxis; PrEP) is under evaluation in clinical trials. Because PrEP is based on antiretrovirals, there is considerable concern that it could substantially increase transmitted resistance, particularly in resource-rich countries. Here we use a mathematical model to predict the effect of PrEP interventions on the HIV epidemic in the men-who-have-sex-with-men community in San Francisco. The model is calibrated using Monte Carlo filtering and analyzed by constructing nonlinear response hypersurfaces. We predict PrEP interventions could substantially reduce transmission but significantly increase the proportion of new infections caused by resistant strains. Two mechanisms can cause this increase. If risk compensation occurs, the proportion increases due to increasing transmission of resistant strains and decreasing transmission of wild-type strains. If risk behavior remains stable, the increase occurs because of reduced transmission of resistant strains coupled with an even greater reduction in transmission of wild-type strains. We define this as the paradox of PrEP (i.e., resistance appears to be increasing, but is actually decreasing). We determine this paradox is likely to occur if the efficacy of PrEP regimens against wild-type strains is greater than 30% and the relative efficacy against resistant strains is greater than 0.2 but less than the efficacy against wild-type. Our modeling shows, if risk behavior increases, that it is a valid concern that PrEP could significantly increase transmitted resistance. However, if risk behavior remains stable, we find the concern is unfounded and PrEP interventions are likely to decrease transmitted resistance.

A universal long-term flu vaccine may not prevent severe epidemics

BACKGROUND

Recently, the promise of a new universal long-term flu vaccine has become more tangible than ever before. Such a vaccine would protect against very many seasonal and pandemic flu strains for many years, making annual vaccination unnecessary. However, due to complacency behavior, it remains unclear whether the introduction of such vaccines would maintain high and stable levels of vaccination coverage year after year.

FINDINGS

To predict the impact of universal long-term flu vaccines on influenza epidemics we developed a mathematical model that linked human cognition and memory with the transmission dynamics of influenza. Our modeling shows that universal vaccines that provide short-term protection are likely to result in small frequent epidemics, whereas universal vaccines that provide long-term protection are likely to result in severe infrequent epidemics.

CONCLUSIONS

Influenza vaccines that provide short-term protection maintain risk awareness regarding influenza in the population and result in stable vaccination coverage. Vaccines that provide long-term protection could lead to substantial drops in vaccination coverage and should therefore include an annual epidemic risk awareness programs in order to minimize the risk of severe epidemics.

Evolutionary dynamics of complex networks of HIV drug-resistant strains: the case of San Francisco

Over the past two decades, HIV resistance to antiretroviral drugs (ARVs) has risen to high levels in the wealthier countries of the world, which are able to afford widespread treatment. We have gained insights into the evolution and transmission dynamics of ARV resistance by designing a biologically complex multistrain network model. With this model, we traced the evolutionary history of ARV resistance in San Francisco and predict its future dynamics. By using classification and regression trees, we identified the key immunologic, virologic, and treatment factors that increase ARV resistance. Our modeling shows that 60% of the currently circulating ARV-resistant strains in San Francisco are capable of causing self-sustaining epidemics, because each individual infected with one of these strains can cause, on average, more than one new resistant infection. It is possible that a new wave of ARV-resistant strains that pose a substantial threat to global public health is emerging.

Calculating the potential for within-flight transmission of influenza A (H1N1)

BACKGROUND

Clearly air travel, by transporting infectious individuals from one geographic location to another, significantly affects the rate of spread of influenza A (H1N1). However, the possibility of within-flight transmission of H1N1 has not been evaluated; although it is known that smallpox, measles, tuberculosis, SARS and seasonal influenza can be transmitted during commercial flights. Here we present the first quantitative risk assessment to assess the potential for within-flight transmission of H1N1.

METHODS

We model airborne transmission of infectious viral particles of H1N1 within a Boeing 747 using methodology from the field of quantitative microbial risk assessment.

RESULTS

The risk of catching H1N1 will essentially be confined to passengers travelling in the same cabin as the source case. Not surprisingly, we find that the longer the flight the greater the number of infections that can be expected. We calculate that H1N1, even during long flights, poses a low to moderate within-flight transmission risk if the source case travels First Class. Specifically, 0-1 infections could occur during a 5 hour flight, 1-3 during an 11 hour flight and 2-5 during a 17 hour flight. However, within-flight transmission could be significant, particularly during long flights, if the source case travels in Economy Class. Specifically, two to five infections could occur during a 5 hour flight, 5-10 during an 11 hour flight and 7-17 during a 17 hour flight. If the aircraft is only partially loaded, under certain conditions more infections could occur in First Class than in Economy Class. During a 17 hour flight, a greater number of infections would occur in First Class than in Economy if the First Class Cabin is fully occupied, but Economy class is less than 30% full.

CONCLUSIONS

Our results provide insights into the potential utility of air travel restrictions on controlling influenza pandemics in the winter of 2009/2010. They show travel by one infectious individual, rather than causing a single outbreak of H1N1, could cause several simultaneous outbreaks. These results imply that, during a pandemic, quarantining passengers who travel in Economy on long-haul flights could potentially be an important control strategy. Notably, our results show that quarantining passengers who travel First Class would be unlikely to be an effective control strategy.

Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)

Here we present a review of the literature of influenza modeling studies, and discuss how these models can provide insights into the future of the currently circulating novel strain of influenza A (H1N1), formerly known as swine flu. We discuss how the feasibility of controlling an epidemic critically depends on the value of the Basic Reproduction Number (R0). The R0 for novel influenza A (H1N1) has recently been estimated to be between 1.4 and 1.6. This value is below values of R0 estimated for the 1918-1919 pandemic strain (mean R0 approximately 2: range 1.4 to 2.8) and is comparable to R0 values estimated for seasonal strains of influenza (mean R0 1.3: range 0.9 to 2.1). By reviewing results from previous modeling studies we conclude it is theoretically possible that a pandemic of H1N1 could be contained. However it may not be feasible, even in resource-rich countries, to achieve the necessary levels of vaccination and treatment for control. As a recent modeling study has shown, a global cooperative strategy will be essential in order to control a pandemic. This strategy will require resource-rich countries to share their vaccines and antivirals with resource-constrained and resource-poor countries. We conclude our review by discussing the necessity of developing new biologically complex models. We suggest that these models should simultaneously track the transmission dynamics of multiple strains of influenza in bird, pig and human populations. Such models could be critical for identifying effective new interventions, and informing pandemic preparedness planning. Finally, we show that by modeling cross-species transmission it may be possible to predict the emergence of pandemic strains of influenza.

Effectiveness and efficiency of imperfect therapeutic HSV-2 vaccines

BACKGROUND

Efforts are currently underway to develop therapeutic vaccines for Herpes Simplex Virus type 2 (HSV-2).

METHODS

We use a mathematical model to predict the potential public health impact of imperfect, therapeutic HSV-2 vaccines. We evaluate vaccine effectiveness and efficiency for the general population in the United States where HSV-2 prevalence is currently 22%. We assume that therapeutic vaccines will produce two therapeutic benefits in vaccinated infected-individuals: (i) the rate of viral reactivation will decrease (hence infected-individuals will experience fewer viral shedding episodes), and (ii) the average length of the viral shedding episodes will be shortened. In addition, we assume that therapeutic vaccines will benefit uninfected individuals by reducing viral shedding in (and hence transmission from) vaccinated infected-individuals.

RESULTS

Our predictions show that therapeutic vaccines could substantially reduce HSV-2 epidemics by reducing new infections by 77% and preventing 0.84 new infections for each vaccinated individual. These vaccines could prevent 212,600 (median; IQR, 156,064-288,558) new infections after only one year. We show that increased effectiveness and efficiency are more strongly correlated with a vaccine-induced reduction in transmission probability than with either of the two therapeutic benefits that accrue directly to the infected individuals (specifically, the reduction in episode length and number of episodes).

CONCLUSIONS

We suggest that current vaccine development efforts target mechanisms that reduce viral shedding (thereby reducing transmission) thus providing both a beneficial therapeutic and a beneficial epidemic-level impact. Our results also demonstrate that therapeutic vaccines would be substantially more useful than prophylactic vaccines for epidemic control.

Modelling an outbreak of an emerging pathogen

To illustrate the usefulness of mathematical models to the microbiology and medical communities, we explain how to construct and apply a simple transmission model of an emerging pathogen. We chose to model, as a case study, a large (>8,000 reported cases) on-going outbreak of community-acquired meticillin-resistant Staphylococcus aureus (CA-MRSA) in the Los Angeles County Jail. A major risk factor for CA-MRSA infection is incarceration. Here, we show how to design a within-jail transmission model of CA-MRSA, parameterize the model and reconstruct the outbreak. The model is then used to assess the severity of the outbreak, predict the epidemiological consequences of a catastrophic outbreak and design effective interventions for outbreak control.

Mean-field analysis of an inductive reasoning game: application to influenza vaccination

Recently we have introduced an inductive reasoning game of voluntary yearly vaccination to establish whether or not a population of individuals acting in their own self-interest would be able to prevent influenza epidemics. Here, we analyze our model to describe the dynamics of the collective yearly vaccination uptake. We discuss the mean-field equations of our model and first order effects of fluctuations. We explain why our model predicts that severe epidemics are periodically expected even without the introduction of pandemic strains. We find that fluctuations in the collective yearly vaccination uptake induce severe epidemics with an expected periodicity that depends on the number of independent decision makers in the population. The mean-field dynamics also reveal that there are conditions for which the dynamics become robust to the fluctuations. However, the transition between fluctuation-sensitive and fluctuation-robust dynamics occurs for biologically implausible parameters. We also analyze our model when incentive-based vaccination programs are offered. When a family-based incentive is offered, the expected periodicity of severe epidemics is increased. This results from the fact that the number of independent decision makers is reduced, increasing the effect of the fluctuations. However, incentives based on the number of years of prepayment of vaccination may yield fluctuation-robust dynamics where severe epidemics are prevented. In this case, depending on prepayment, the transition between fluctuation-sensitive and fluctuation-robust dynamics may occur for biologically plausible parameters. Our analysis provides a practical method for identifying how many years of free vaccination should be provided in order to successfully ameliorate influenza epidemics.

How far will we need to go to reach HIV-infected people in rural South Africa?

BACKGROUND

The South African Government has outlined detailed plans for antiretroviral (ART) rollout in KwaZulu-Natal Province, but has not created a plan to address treatment accessibility in rural areas in KwaZulu-Natal. Here, we calculate the distance that People Living With HIV/AIDS (PLWHA) in rural areas in KwaZulu-Natal would have to travel to receive ART. Specifically, we address the health policy question 'How far will we need to go to reach PLWHA in rural KwaZulu-Natal?'.

METHODS

We developed a model to quantify treatment accessibility in rural areas; the model incorporates heterogeneity in spatial location of HCFs and patient population. We defined treatment accessibility in terms of the number of PLWHA that have access to an HCF. We modeled the treatment-accessibility region (i.e. catchment area) around an HCF by using a two-dimensional function, and assumed that treatment accessibility decreases as distance from an HCF increases. Specifically, we used a distance-discounting measure of ART accessibility based upon a modified form of a two-dimensional gravity-type model. We calculated the effect on treatment accessibility of: (1) distance from an HCF, and (2) the number of HCFs.

RESULTS

In rural areas in KwaZulu-Natal even substantially increasing the size of a small catchment area (e.g. from 1 km to 20 km) around an HCF would have a negligible impact (~2%) on increasing treatment accessibility. The percentage of PLWHA who can receive ART in rural areas in this province could be as low as ~16%. Even if individuals were willing (and able) to travel 50 km to receive ART, only ~50% of those in need would be able to access treatment. Surprisingly, we show that increasing the number of available HCFs for ART distribution ~ threefold does not lead to a threefold increase in treatment accessibility in rural KwaZulu-Natal.

CONCLUSION

Our results show that many PLWHA in rural KwaZulu-Natal are unlikely to have access to ART, and that the impact of an additional 37 HCFs on treatment accessibility in rural areas would be less substantial than might be expected. There is a great length to go before we will be able to reach many PLWHA in rural areas in South Africa, and specifically in KwaZulu-Natal.

Longitudinal study of herpes simplex virus type 2 infection using viral dynamic modelling

OBJECTIVES

Rates of reactivation of herpes simplex virus type 2 (HSV-2) change over time and these changes affect transmission and clinical management strategies. We conducted a longitudinal study of HSV-2 infection to quantify rates of change in HSV-2 reactivation, mucosal shedding and recurrences of genital lesions, using a newly available model of HSV within-host dynamics.

METHODS

A cohort of 18 women was studied at two time periods spaced 2 years apart. The cohort provided daily mucosal swabs for HSV PCR analysis for 10 weeks during each time period and recorded recurrences in diaries. We fit the model of HSV dynamics to the mucosal shedding data using Bayesian methods to produce estimates of HSV reactivation, shedding and longitudinal rates of change. The model was validated using a separate group of 67 individuals.

RESULTS

According to the viral dynamic modelling results, rates of HSV-2 reactivation from latency in the ganglia varied >10-fold among the women, and were estimated to be > or = 10% higher than rates of mucosal shedding episodes for many individuals. The mucosal shedding associated with each reactivation typically lasted 1-3 days. Reactivation frequency was estimated to be declining by three reactivations a year on average. The median number of recurrences, based on patient diaries, declined from 6.8 per year to 2.1 per year over the 2-year period.

CONCLUSIONS

Rates of HSV-2 reactivation, shedding and recurrence generally decline over time but remain high in some individuals 4-5 years after primary infection. Viral dynamic modelling provides quantification of HSV infection that cannot be obtained by other methods.