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Biology subjects

Nyasebwa, O. M.

Publications and source records attributed to Nyasebwa, O. M..

3 recordsLinked to original sources

The value of livestock abortion surveillance in Tanzania: identifying disease priorities and informing interventions

BackgroundLack of reliable data on the aetiology of livestock diseases, especially in Africa, is a major factor constraining the design of effective livestock health interventions to improve livelihoods, food security and public health. RationaleLivestock abortion is an important disease syndrome that affects productivity and livestock economies, and poses risks to public health. Worldwide, several pathogens are associated with livestock abortions but across Africa livestock disease surveillance data rarely include information from abortion events, little is known about the aetiology and impacts of livestock abortions, and data are not available to inform prioritisation of disease interventions. MethodsThis paper describes outcomes from a surveillance platform that was set up in 15 wards in northern Tanzania spanning pastoral, agropastoral and smallholder agro-ecological systems to investigate the causes and impacts of livestock abortion. Abortion cases were reported by farmers to Ministry of Livestock and Fisheries livestock field officers and on to investigation teams. The abortion was eligible for inclusion if the research field team or livestock field officer could attend within 72 hours of the event occurring. If so, a field investigation was carried out to collect diagnostic samples from aborted materials and aborting dams and questionnaire data on herd/flock management. Laboratory diagnostic tests were carried out for a range of abortigenic pathogens, and laboratory and questionnaire data analysed to investigate a) determinants of attribution; b) patterns of investigated events, including species and breed affected, previous abortion history and recent stressful events, and the seasonality of cases; c) determinants of reporting, investigation and attribution; (d) cases in which zoonotic pathogens were detected. ResultsOver a two-year period (2017-2019), 215 abortion events in cattle (n=71), sheep (n=44) and goats (n=100) were investigated from 13 of the 15 wards. The number of investigated cases varied widely across wards, with three of the 15 field officers (20%) reporting 70% of investigated cases. Aetiological attribution, achieved for 19.5% of cases through PCR-based diagnostics, was significantly affected by delays in obtaining samples from field investigation. Histopathology proved less useful than PCR diagnostics due to rapid deterioration of field samples. Vaginal swabs from aborting dams provided a practical and sensitive source of diagnostic material for pathogen detection. Discussion / ConclusionLivestock abortion surveillance, even at a small scale and when capturing only a small proportion of events, can generate valuable information on causes of zoonotic disease outbreaks, livestock reproductive losses and can identify important pathogens that are not easily captured through other forms of livestock disease surveillance. This study demonstrated the feasibility of establishing an effective reporting and investigation system that could be implemented across a range of settings, including remote rural areas. This has been achieved through effective engagement of community-based field officers, establishment of practical sample collection protocols and application of molecular diagnostic platforms.

zoology↗

Modelling the effectiveness of targeting Rift Valley fever virus vaccination using imperfect network information

Livestock movements contribute to the spread of several infectious diseases. Data on livestock movements can therefore be harnessed to guide policy on targeted interventions for controlling infectious livestock diseases, including Rift Valley fever (RVF) -- a vaccine-preventable arboviral fever. While detailed livestock movement data are available in many countries, such data are generally lacking in others, including many in East Africa, where multiple RVF outbreaks have been reported in recent years. Available movement data are imperfect, and the impact of imperfect movement data on targeted vaccination is not fully understood. Here, we used a network simulation model to describe the spread of RVF within and between 398 wards in northern Tanzania connected by cattle movements, on which we evaluated the impact of targeting vaccination using imperfect movement data. We show that pre-emptive vaccination guided by only market movement permit data could prevent large outbreaks. Targeted control (either by the risk of RVF introduction or onward transmission) at any level of imperfect movement information is preferred over random vaccination, and any improvement in information reliability is advantageous to their effectiveness. Our modelling approach demonstrates how targeted interventions can be carefully applied to inform animal and public health policies on disease control planning in settings where detailed data on livestock movements are unavailable or imperfect due to a lack of data-gathering resources.

genetics↗

An outbreak of Rift Valley fever among peri-urban dairy cattle in northern Tanzania, 2018

Undetected Rift Valley fever (RVF) outbreaks are expected in endemic countries but little is known about their size or frequency. We describe a previously unreported RVF outbreak involving dairy cattle that appeared to be limited to the edge of the town of Moshi, Tanzania and occurred from May through August, 2018. The outbreak was detected retrospectively using samples collected as part of a cohort study investigating the causes of livestock abortion across northern Tanzania. A total of 14 RVF-associated cattle abortions were identified using a combination of serology and quantitative reverse transcription PCR (RT-qPCR). Milk samples from three (21%) of 14 cases were also RT-qPCR positive. Genotyping revealed circulation of RVF viruses from two lineages. The occurrence of an RVF outbreak among peri-urban dairy cattle, and evidence for RVF viral shedding in milk, highlights the potential for emerging zoonotic risks associated with the growth of urban and peri-urban livestock populations.

ecology↗