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Introduction: The decision-making process for malaria control and elimination strategies has become more challenging. Interventions need to be targeted at council level to allow for changing malaria epidemiology and an increase in the number of possible interventions. Models of malaria dynamics can support this process by simulating potential impacts of multiple interventions in different settings and determining appropriate packages of interventions for meeting specific expected targets., Methods: The OpenMalaria model of malaria dynamics was calibrated for all 184 councils in mainland Tanzania using data from malaria indicator surveys, school parasitaemia surveys, entomological surveillance, and vector control deployment data. The simulations were run for different transmission intensities per region and five interventions, currently or potentially included in the National Malaria Strategic Plan, individually and in combination. The simulated prevalences were fitted to council specific prevalences derived from geostatistical models to obtain council specific predictions of the prevalence and number of cases between 2017 and 2020. The predictions were used to evaluate in silico the feasibility of the national target of reaching a prevalence of below 1% by 2020, and to suggest alternative intervention stratifications for the country., Results: The historical prevalence trend was fitted for each council with an agreement of 87% in 2016 (95%CI: 0.84-0.90) and an agreement of 90% for the historical trend (2003-2016) (95%CI: 0.87-0.93) The current national malaria strategy was expected to reduce the malaria prevalence between 2016 and 2020 on average by 23.8% (95% CI: 19.7%-27.9%) if current case management levels were maintained, and by 52.1% (95% CI: 48.8%-55.3%) if the case management were improved. Insecticide treated nets and case management were the most cost-effective interventions, expected to reduce the prevalence by 25.0% (95% CI: 19.7%-30.2) and to avert 37 million cases between 2017 and 2020. Mass drug administration was included in most councils in the stratification selected for meeting the national target at minimal costs, expected to reduce the prevalence by 77.5% (95%CI: 70.5%-84.5%) and to avert 102 million cases, with almost twice higher costs than those of the current national strategy. In summary, the model suggested that current interventions are not sufficient to reach the national aim of a prevalence of less than 1% by 2020 and a revised strategic plan needs to consider additional, more effective interventions, especially in high transmission areas and that the targets need to be revisited., Conclusion: The methodology reported here is based on intensive interactions with the NMCP and provides a helpful tool for assessing the feasibility of country specific targets and for determining which intervention stratifications at sub-national level will have most impact. This country-led application could support strategic planning of malaria control in many other malaria endemic countries., Competing Interests: The authors have declared that no competing interests exist.

Manual hand counting of parasites in fecal samples requires costly components and substantial expertise, limiting its use in resource-constrained settings and encouraging overuse of prophylactic medication. To address this issue, a cost-effective, automated parasite diagnostic system that does not require special sample preparation or a trained user was developed. It is composed of an inexpensive (~US$350), portable, robotic microscope that can scan over the size of an entire McMaster chamber (100 mm 2 ) and capture high-resolution (~1 μm lateral resolution) bright field images without need for user intervention. Fecal samples prepared using the McMaster flotation method were imaged, with the imaging region comprising the entire McMaster chamber. These images are then automatically segmented and analyzed using a trained convolution neural network (CNN) to robustly separate eggs from background debris. Simple postprocessing of the CNN output yields both egg species and egg counts. The system was validated by comparing accuracy with hand-counts by a trained operator, with excellent performance. As a further demonstration of utility, the system was used to conveniently quantify drug response over time in a single animal, showing residual disease due to Anthelmintic resistance after 2 weeks., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)