Background: In livestock disease surveillance, spatial analysis methods play a major role in the identification of areas where the risk of disease could be higher. Though widely used in human health, their extent and depth of use are not well known in livestock health in sub-Saharan Africa and this has hindered their update in livestock disease modeling. This study set out to provide a comprehensive review of spatial analysis methods and their application in livestock disease data analysis in sub-Saharan Africa. Methods: Articles were searched using keywords related to spatial and spatio-temporal analysis of livestock diseases in sub-Saharan Africa in PubMed, Web of Science, Embase, and Scopus. Articles were reviewed in terms of name of author, country of study area, study design, livestock species, livestock diseases, research tasks, and spatial epidemiological methods in terms of spatial statistics and models among others. Results: A total of 56 articles were selected for review. Descriptive approaches such as simple maps of incidence and prevalence (n = 22) have been commonly used. Spatial scan statistics of the Kulldorff (n = 15) have also been the common spatial statistics employed. Model based spatial analysis has also been used (n = 14). Key research tasks that have been performed include investigating disease distribution, risk factors, space and time interaction and spatial risk prediction. The shortfalls of the reviewed studies include lack of exploration of irregularly shaped cluster scan statistics in case the actual disease clusters are irregular. There is also lack of use of multivariate scan and joint spatial models in case of multiple groups or diseases to show comorbidity. Model based spatial analysis has not accounted for space and time interaction. Machine learning niche models have failed to account for spatial autocorrelation in the data. Model based spatial risk prediction has mainly been retrospective as opposed to prospective for early warning. Conclusion: Future research may consider the application of multivariate scan statistics and joint spatial models for disease comorbidity analysis. It may also explore the use of irregularly shaped cluster scan statistics to enable detection of irregular disease clusters. Research opportunities may also include the use of machine learning models that account for spatial autocorrelation. Future

Introduction During household surveys, vaccination coverage is commonly estimated through vaccination cards and parental recall. Although data from vaccination cards are more reliable than parental recall, both approaches are prone to selection and information bias. At times, vaccination cards may not be available because of loss or misplacement necessitating the use of parental recall as alternative. In this study, the validity of the vaccination coverage from these two sources were compared. Individual and household level factors associated with recall bias were also assessed. Methods The vaccination coverage of the parental recall and vaccination card were calculated separately for each of the vaccines. The level of agreement was computed between the estimates from the parental recall and vaccination cards. Sensitivity and specificity of parental recall were computed. The study also examined the factors that would be associated with recall bias. Multiple logistic regression model by vaccine type were fitted where odds ratios and 95% confidence intervals were reported. Results The vaccination coverage for BCG was 98.6 for card-based and 98.1 for parental recall. The vaccination coverage for OPV was 98.9 for card-based and 98.1 for parental recall. For PCV, it was 99.6 for card-based and 97.4 for parental recall. For measles was 84.1 for card-based and 88.0 for parental recall. The results show a high level of agreement between parental recall and card-based (>97%) across all vaccines. The parental recall bias was minimal ranging from 1.13 to 6.66. The sensitivity of parental recall was almost 100% with low specificity. Factors such as parental and child age was associated with parental recall bias for PCV and measles Conclusion The study has demonstrated and supported the need to use the parental recall to estimate the vaccination coverage for different vaccine types which can be used instead of or in the absence of card-based data or records.

Background The RTS,S/AS01 malaria vaccine was introduced in Ghana, Kenya, and Malawi in 2019. Evaluation includes case-control studies designed to monitor individual-level safety and effectiveness to complement population-level estimates derived from the MVPE. Here, we discuss design and practical considerations for conducting case-control studies to measure vaccine effectiveness against severe malaria, the need for a 4th dose, and for assessment of safety outcomes. Methods For the severe malaria study we aimed to estimate the effectiveness of the primary 3 doses, and of the 4th dose. We also aimed to estimate rebound, if any, in children who received only the primary 3 doses. Cases were patients with severe malaria admitted to a study hospital, residing in an RTS,S/AS01 implementation area, and eligible to have received the 3rd or 4th dose of the vaccine. The case patient’s home is visited to collect data on vaccination status and other details. Four controls are then recruited from the same community, matched closely on date of birth. Vaccination status is determined from home-based records, and from clinic registers. Similar approaches were used for studies of safety outcomes. Results We share preliminary results and discuss the challenges encountered and lessons learned about implementing a multi-centre case control study for a malaria vaccine, and approaches to data collection which have proved effective, including establishing surveillance, the use of specific case definitions standardized across centres, recruiting closely age-matched community controls, and obtaining reliable information from both cases and controls on potential confounding factors which may be associated with both risk of the outcome and with access to vaccination. Conclusion Case control studies are an efficient means of monitoring vaccine effectiveness and safety, but require care in design and implementation. The lessons learned from the malaria vaccine pilots will be useful for countries planning introduction of a malaria vaccine.