Background In order to protect health workers from SARS-CoV-2, there is need to characterise the different types of patient facing health workers. Our first aim was to determine both the infection and seroprevalence of SARS-COV-2 in health workers. Our second aim was to evaluate the occupational and demographic predictors of seropositivity to inform the country’s infection prevention and control (IPC) strategy. Methods and principal findings We invited 713 staff members at 24 out of 35 health facilities in the City of Bulawayo in Zimbabwe. Compliance to testing was defined as the willingness to uptake COVID-19 testing by answering a questionnaire and providing samples for both antibody testing and PCR testing. SARS-COV-2 antibodies were detected using a rapid diagnostic test kit and SAR-COV-2 infection was determined by real-time (RT)- PCR. Of the 713 participants, 635(89%) consented answering the questionnaire and providing blood sample for antibody testing while 560 (78.5%) agreed to provide nasopharyngeal swabs for the PCR COVID-19 testing. Of the 635 people (aged 18–73) providing a blood sample 39.1% reported a history of past COVID-19 symptoms while 14.2% reported having current symptoms of COVID-19. The most-prevalent co-morbidity among this group was hypertension (22.0%) followed by asthma (7.0%) and diabetes (6.0%). The SARS-CoV-2 sero-prevalence was 8.9%. Of the 560 participants tested for SARS-CoV-2 infection, 2 participants (0.36%) were positive for SAR-CoV-2 infection by PCR testing. None of the SARS-CoV-2 antibody positive people were positive for SAR-CoV-2 infection by PCR testing. Conclusion and interpretation In addition to clinical staff, several patient-facing health workers were characterised within Zimbabwe’s health system and the seroprevalence data indicated that previous exposure to SAR-CoV-2 had occurred across the full spectrum of patient-facing staff with nurses and nurse aides having the highest seroprevalence. Our results highlight the need for including the various health workers in IPC strategies in health centres to ensure effective biosecurity and biosafety.

Development and agriculture are increasingly encroaching into riparian areas, with largely unknown effects on nearshore arthropods, which are important components of linked aquatic–terrestrial food webs. To assess the environmental determinants of the distribution and trophic dynamics of riparian spiders of the family Tetragnathidae, we characterised riparian habitat, collected emergent aquatic insects, and surveyed spiders in developed and rural landscapes of the Scioto River system, Ohio, USA, which provided a range of riparian land cover, nearshore vegetation types and habitat complexity. We also estimated the trophic position (TP) of Tetragnathidae and the proportion of energetic and nutritional subsidies derived from benthic algae (EBA) using naturally abundant carbon (C) and nitrogen (N) stable isotopes. Model-selection results revealed that tetragnathid spider density (1.57–3.80individualsm–1) was more sensitive to differences in overhanging vegetation than to those in aquatic food resources (i.e. emergent aquatic insects). Tetragnathidae TP, which averaged 3.16 across all 12 study reaches (range: 2.35–3.98), was largely driven by canopy density, shoreline shape, percentage overhanging vegetation and emergent-insect density. Emergent-insect density was the strongest driver of tetragnathid spider EBA (0.04–0.54, µ=0.24). Our study reinforced the notion that riparian spiders ecologically link aquatic and terrestrial ecosystems. In particular, our results further current understanding of the mechanisms affecting riparian spider distribution and trophic dynamics, particularly in the context of larger stream and river systems, given that the propensity of related research has occurred in small streams.

The central role of species competition in shaping community structure in ecosystems is well appreciated amongst ecologists. However species competition is a consistently missing variable in Species Distribution Modelling (SDM). This study presents results of our attempt to incorporate species competition in SDMs. We used a suit of predictor variables including Soil Adjusted Vegetation Index (SAVI), as well as distance from roads, settlements and water, fire frequency and distance from the nearest herbivore sighting (of selected herbivores) to model individual habitat preferences of five grazer species (buffalo, warthog, waterbuck, wildebeest and zebra) with the Ensemble SDM algorithm for Gonarezhou National Park, Zimbabwe. Our results showed that distance from the nearest animal sighting (a proxy for competition among grazers) was the best predictor of the potential distribution of buffalo, wildebeest and zebra but the second best predictor for warthog and waterbuck. Our findings provide evidence to that competition is an important predictor of grazer species’ potential distribution. These findings suggest that species distribution modelling that neglects species competition may be inadequate in explaining the potential distribution of species. Therefore our findings encourage the inclusion of competition in SDM as well as potentially igniting discussions that may lead to improving the predictive power of future SDM efforts.

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