A paper-based disease reporting system has been associated with a number of challenges. These include difficulties to submit hard copies of the disease surveillance forms because of poor road infrastructure, weather conditions or challenging terrain, particularly in the developing countries. The system demands re-entry of the data at data processing and analysis points, thus making it prone to introduction of errors during this process. All these challenges contribute to delayed acquisition, processing and response to disease events occurring in remote hard to reach areas. Our study piloted the use of mobile phones in order to transmit near to real-time data from remote districts in Tanzania (Ngorongoro and Ngara), Burundi (Muyinga) and Zambia (Kazungula and Sesheke). Two technologies namely, digital and short messaging services were used to capture and transmit disease event data in the animal and human health sectors in the study areas based on a server-client model. Smart phones running the Android operating system (minimum required version: Android 1.6), and which supported open source application, Epicollect, as well as the Open Data Kit application, were used in the study. These phones allowed collection of geo-tagged data, with the opportunity of including static and moving images related to disease events. The project supported routine disease surveillance systems in the ministries responsible for animal and human health in Burundi, Tanzania and Zambia, as well as data collection for researchers at the Sokoine University of Agriculture, Tanzania. During the project implementation period between 2011 and 2013, a total number of 1651 diseases event-related forms were submitted, which allowed reporters to include GPS coordinates and photographs related to the events captured. It was concluded that the new technology-based surveillance system is useful in providing near to real-time data, with potential for enhancing timely response in rural remote areas of Africa. We recommended adoption of the proven technologies to improve disease surveillance, particularly in the developing countries.

A paper-based disease reporting system has been associated with a number of challenges. These include difficulties to submit hard copies of the disease surveillance forms because of poor road infrastructure, weather conditions or challenging terrain, particularly in the developing countries. The system demands re-entry of the data at data processing and analysis points, thus making it prone to introduction of errors during this process. All these challenges contribute to delayed acquisition, processing and response to disease events occurring in remote hard to reach areas. Our study piloted the use of mobile phones in order to transmit near to real-time data from remote districts in Tanzania (Ngorongoro and Ngara), Burundi (Muyinga) and Zambia (Kazungula and Sesheke). Two technologies namely, digital and short messaging services were used to capture and transmit disease event data in the animal and human health sectors in the study areas based on a server–client model. Smart phones running the Android operating system (minimum required version: Android 1.6), and which supported open source application, Epicollect, as well as the Open Data Kit application, were used in the study. These phones allowed collection of geo-tagged data, with the opportunity of including static and moving images related to disease events. The project supported routine disease surveillance systems in the ministries responsible for animal and human health in Burundi, Tanzania and Zambia, as well as data collection for researchers at the Sokoine University of Agriculture, Tanzania. During the project implementation period between 2011 and 2013, a total number of 1651 diseases event-related forms were submitted, which allowed reporters to include GPS coordinates and photographs related to the events captured. It was concluded that the new technology-based surveillance system is useful in providing near to real-time data, with potential for enhancing timely response in rural remote areas of Africa. We recommended adoption of the proven technologies to improve disease surveillance, particularly in the developing countries.

Peste des petits ruminants (PPR) is an acute viral disease of small ruminants characterised by the sudden onset of depression, fever, oculonasal discharges, sores in the mouth, foul-smelling diarrhoea and death. For many years, in Africa, the disease was mainly confined to West and Central Africa but it has now spread southwards to previously PPR-free countries including Tanzania, Democratic Republic of Congo and Angola. The disease was first reported in Tanzania in 2008 when it was confined to the Northern Zone districts bordering Kenya. Presence of the disease has also been confirmed in southern Tanzania especially Mtwara region. Recently, a suspected outbreak of PPR in Dakawa area, Mvomero district, Morogoro region was reported. Clinical samples (lungs, intestines, lymph nodes, whole blood and sera) from suspected goats (n = 8) and sheep (n = 1) were submitted to Sokoine University of Agriculture for analysis. Molecular diagnosis by amplification of the nucleoprotein gene and the fusion gene of PPR virus (PPRV) using PPRV specific primers was done. Five goats and the sheep were positive for PPRV after performing RT-PCR. To our knowledge, this is the first report confirming the presence of PPR in the Mvomero district of the Morogoro region, Tanzania. Hence, more efforts should be put in place to prevent the spread of PPR in Tanzania.

Peste des petits ruminants (PPR) is an acute viral disease of small ruminants characterised by the sudden onset of depression, fever, oculonasal discharges, sores in the mouth, foul-smelling diarrhoea and death. For many years, in Africa, the disease was mainly confined to West and Central Africa but it has now spread southwards to previously PPR-free countries including Tanzania, Democratic Republic of Congo and Angola. The disease was first reported in Tanzania in 2008 when it was confined to the Northern Zone districts bordering Kenya. Presence of the disease has also been confirmed in southern Tanzania especially Mtwara region. Recently, a suspected outbreak of PPR in Dakawa area, Mvomero district, Morogoro region was reported. Clinical samples (lungs, intestines, lymph nodes, whole blood and sera) from suspected goats (n = 8) and sheep (n = 1) were submitted to Sokoine University of Agriculture for analysis. Molecular diagnosis by amplification of the nucleoprotein gene and the fusion gene of PPR virus (PPRV) using PPRV specific primers was done. Five goats and the sheep were positive for PPRV after performing RT-PCR. To our knowledge, this is the first report confirming the presence of PPR in the Mvomero district of the Morogoro region, Tanzania. Hence, more efforts should be put in place to prevent the spread of PPR in Tanzania.

The global focus on wildlife as a major contributor to emerging pathogens and infectious diseases (EIDs) in humans and domestic animals is not based on field, experimental or dedicated research, but mostly on limited surveys of literature, opinion and the assumption that biodiversity harbours pathogens. The perceived and direct impacts of wildlife, from being a reservoir of certain human and livestock pathogens and as a risk to health, are frequently overstated when compared to the Global burden of disease statistics available from WHO, OIE and FAO. However organisms that evolve in wildlife species can and do spill-over into human landscapes and humans and domestic animal population and, where these organisms adapt to surviving and spreading amongst livestock and humans, these emerging infections can have significant consequences. Drivers for the spill-over of pathogens or evolution of organisms from wildlife reservoirs to become pathogens of humans and domestic animals are varied but almost without exception poorly researched. The changing demographics, spatial distribution and movements, associated landscape modifications (especially agricultural) and behavioural changes involving human and domestic animal populations are probably the core drivers of the apparent increasing trend in emergence of new pathogens and infectious diseases over recent decades.

The global focus on wildlife as a major contributor to emerging pathogens and infectious diseases (EIDs) in humans and domestic animals is not based on field, experimental or dedicated research, but mostly on limited surveys of literature, opinion and the assumption that biodiversity harbours pathogens. The perceived and direct impacts of wildlife, from being a reservoir of certain human and livestock pathogens and as a risk to health, are frequently overstated when compared to the Global burden of disease statistics available from WHO, OIE and FAO. However organisms that evolve in wildlife species can and do spill-over into human landscapes and humans and domestic animal population and, where these organisms adapt to surviving and spreading amongst livestock and humans, these emerging infections can have significant consequences. Drivers for the spill-over of pathogens or evolution of organisms from wildlife reservoirs to become pathogens of humans and domestic animals are varied but almost without exception poorly researched. The changing demographics, spatial distribution and movements, associated landscape modifications (especially agricultural) and behavioural changes involving human and domestic animal populations are probably the core drivers of the apparent increasing trend in emergence of new pathogens and infectious diseases over recent decades.

The reproductive performance of pigs is one of the main determinants of the profit farmers make from pig production. This study was undertaken to describe whether periods of high environmental temperature have an effect on the farrowing rate, litter sizes and number of stillbirths in commercial breeding units in South Africa. Data were collected weekly from four commercial breeding units with good records from December 2010 to August 2012. These data included the number of sows mated, number of sows farrowed and number of piglets born alive, as well as the number of stillbirths. Note was also taken of whether environmental temperature control mechanisms were employed. Temperature data from weather stations within 100 km of the breeding units were obtained from the South African Weather Service. In all breeding units a decrease in farrowing rate following mating during severe average temperatures (> 30 °C) when compared to the farrowing rate following mating during mild average temperatures (< 22 °C) was observed. When mating occurred at higher temperatures, the resultant litter size was marginally decreased in the breeding units that did not employ environmental temperature control, but was unaffected in the breeding units that did. In all four breeding units the trend was for the average number of piglets born alive to increase as the environmental temperature around the time of farrowing increased and the trend in three of the four breeding units was for the percentage of stillbirths per litter to decrease with increased temperature around the time of farrowing. The most significant observation in this study was the trend for farrowing rates to decrease following inseminations during times of high ambient temperatures (> 30 °C). Environmental temperature control did not negate this effect, but the breeding units employing the environmental temperature control did show higher average farrowing rates overall.

There are at least six Lyssavirus species that have been isolated in Africa, which include classical rabies virus, Lagos bat virus, Mokola virus, Duvenhage virus, Shimoni bat virus and Ikoma lyssavirus. In this retrospective study, an analysis of the antigenic reactivity patterns of lyssaviruses in South Africa against a panel of 15 anti-nucleoprotein monoclonal antibodies was undertaken. A total of 624 brain specimens, collected between 2005 and 2009, confirmed as containing lyssavirus antigen by direct fluorescent antibody test, were subjected to antigenic differentiation. The lyssaviruses were differentiated into two species, namely rabies virus (99.5%) and Mokola virus (0.5%). Furthermore, rabies virus was further delineated into two common rabies biotypes in South Africa: canid and mongoose. Initially, it was found that the canid rabies biotype had two reactivity patterns; differential staining was observed with just one monoclonal antibody. This difference was likely to have been an artefact related to sample quality, as passage in cell culture restored staining. Mongoose rabies viruses were more heterogeneous, with seven antigenic reactivity patterns detected. Although Mokola viruses were identified in this study, prevalence and reservoir host species are yet to be established. These data demonstrate the usefulness of monoclonal antibody typing panels in lyssavirus surveillance with reference to emergence of new species or spread of rabies biotypes to new geographic zones.