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Summary Objectives For tuberculosis (TB) transmission to occur, an uninfected individual must inhale the previously infected breath. Our objective was to identify potential TB transmission hotspots in metropolitan city of Dar es Salaam, Tanzania and to model the annual risk of TB transmission in different locations of public importance. Methods We collected indoor carbon dioxide (CO 2 ) data from markets, prisons, night clubs, public transportation, religious and social halls, and from schools. Study volunteers recorded social contacts at each of the locations. We then estimated the annual risks of TB transmission using a modified Wells-Riley equation for different locations. Results The annual risks of TB transmission were highest among prison inmates (41.6%) and drivers (20.3%) in public transport. Lower transmission risks were found in central markets (4.8% for traders, but 0.5% for their customers), passengers on public transport (2.4%), public schools (4.0%), nightclubs (1.7%), religious (0.13%), and social halls (0.12%). Conclusion For the first time in a country representative of sub-Saharan Africa, we modelled the risk of TB transmission in important public locations by using a novel approach of studying airborne transmission. This approach can guide identification of TB transmission hotspots and targeted interventions to reach WHO's ambitious End TB targets. [ABSTRACT FROM AUTHOR]

Abstract: Recent declines in malaria burden in many parts of the world have prompted consideration of how interruption of Plasmodium falciparum transmission could be maintained, if achieved, and notably whether large-scale vector control could be replaced with surveillance. This information is essential for elimination feasibility assessments and planning. The risk of re-establishment of transmission depends mainly on vectorial capacity (receptivity), likely to rebound once vector control is removed, the rate of importation of infections (vulnerability), the capacity to detect and treat infections and the level of immunity in infected individuals. Timely detection and removal of new infections is likely to be critical to prevent re-establishment of transmission. We assess, through mathematical modeling and simulation, which levels of case detection and treatment (case management) are required to prevent re-establishment of transmission of P. falciparum after local interruption of transmission has been achieved, in settings with varying receptivity and vulnerability. We find that, even at rather low levels of receptivity, case management alone cannot reliably prevent re-establishment of P. falciparum malaria transmission in the face of medium to high importation rates. Thus, if vector control is to be discontinued, preventing the importations by controlling transmission in source areas will generally be necessary for preventing reintroduction in such settings, and cannot be substituted by very high levels of case management coverage. [Copyright &y& Elsevier]

Abstract: Objectives: The duration of untreated Plasmodium falciparum infections in naturally exposed human populations is of interest for rational planning of malaria control interventions as it is related to the duration of infectivity. The extent of variability in duration is relevant where transmission is seasonal, and for the planning of elimination efforts. Methods for measuring these quantities from genotyping data have been restricted to exponential models of infection survival, as implied by constant clearance rates. Such models have greatly improved the understanding of infection dynamics on a population level but likely misrepresent the within-host dynamics of many pathogens. Conversely, the statistical properties of the distribution of infection durations, and how these are affected by exposure, should contain information on within-host dynamics. Methods and results: We extended existing methods for the analysis of longitudinal genotyping data on P. falciparum infections. Our method simultaneously estimates force of infection, detectability, and the distribution of infection durations. Infection durations are modeled using parametric survival distributions. The method is validated using simulated data, and applied to data from a cohort study in Navrongo, Northern Ghana. Distribution estimates from exponential, Weibull, lognormal, and gamma models are compared with the distribution of durations in malariatherapy data. Conclusions: The Weibull model fitted the data best. It estimated a shorter mean duration than the exponential model, which gave the worst fit. The distribution estimates appeared positively skewed when compared with the distribution of durations in malariatherapy data, suggesting that a significant proportion of infections is cleared shortly after inoculation. We conclude that malariatherapy data, the most important source of information on P. falciparum within-host dynamics, may not be representative of the actual processes in natural populations, and should be used with care. Further, conclusions from transmission models assuming exponential infection survival may be biased. [Copyright &y& Elsevier]

A quantitative framework is used to explore the potential applications and probable effects of sexual stage or mosquito stage transmission blocking vaccines (TBVs) against malaria. The combination of TBVs with biocides or other malaria vaccines will increase chances of interrupting transmission, whereas the value of TBVs for morbidity control will be limited. Vaccine combination will also protect against selection of insensitive parasites. Simulations indicate that TBVs will reduce risks of reestablishment of transmission when vector control is withdrawn. Simple mathematical analysis shows that efficacy and coverage are equally important, implying that a vaccine that requires a small number of doses (ideally one) is preferable to one that is difficult to deliver, even if this entails accepting a lower efficacy. [Copyright &y& Elsevier]

Highlights: [•] Accurate measures of transmission are necessary for malaria elimination. [•] Different settings are conducive to different measures of transmission. [•] Mathematical models provide a means to translate between different measures of transmission and disease burden. [•] The effect of seasonality on the relationship between malaria measures is crucial. [ABSTRACT FROM AUTHOR]

Trypanosoma brucei gambiense causes human African trypanosomiasis (HAT). Between 1990 and 2015, almost 440 000 cases were reported. Large-scale screening of populations at risk, drug donations, and efforts by national and international stakeholders have brought the epidemic under control with <2200 cases in 2016. The World Health Organization (WHO) has set the goals of gambiense -HAT elimination as a public health problem for 2020, and of interruption of transmission to humans for 2030. Latent human infections and possible animal reservoirs may challenge these goals. It remains largely unknown whether, and to what extend, they have an impact on gambiense -HAT transmission. We argue that a better understanding of the contribution of human and putative animal reservoirs to gambiense- HAT epidemiology is mandatory to inform elimination strategies. [ABSTRACT FROM AUTHOR]