Occurrence of 4 Dengue Virus Serotypes and Chikungunya Virus in Kilombero Valley, Tanzania, During the Dengue Outbreak in 2018.

BACKGROUND: Dengue and Chikungunya viruses can cause large-scale epidemics, with attack rates of up to 80%. In Tanzania, there have been repeated outbreaks of dengue fever, the most recent in 2018 and 2019, mostly affecting the coastal areas. Despite the importance of these viruses, there is limited knowledge on the epidemiology of dengue (DENV) and Chikungunya (CHIKV) in Tanzania. This study was conducted to investigate the prevalence of DENV and CHIKV in Kilombero Valley, Tanzania. METHODS: A cross-sectional study was conducted at Kibaoni Health Center in Kilombero Valley, Southeastern Tanzania, in the rainy and dry seasons of 2018. Febrile patients of any age and gender were enrolled from the outpatient department. Blood samples were taken and screened for DENV and CHIKV viral RNA by real-time reverse transcription polymerase chain reaction assays. RESULTS: Overall, 294 patients were recruited. Most were females (65%), and one-third of patients were aged 14-25 years. DENV and CHIKV were detected in 29 (9.9%) and 3 (1.0%) patients, respectively. DENV was detected across all age groups during both the dry and rainy seasons. Although all 4 DENV serotypes were detected, serotypes 1 and 3 dominated and were present in 14 patients (42.4%) each. Additionally, the study showed DENV-1 and DENV-3 co-infections. CONCLUSIONS: This study reveals the co-circulation of all 4 DENV serotypes and CHIKV in Kilombero. Importantly, we report the first occurrence of DENV-4 in Tanzania. Unlike previous DENV outbreaks caused by DENV-2, the 2018 outbreak was dominated by DENV-1 and DENV-3. The occurrence of all serotypes suggests the possibility of severe clinical outcomes in future DENV epidemics in Tanzania.

Crowdsourcing Vector Surveillance: Using Community Knowledge and Experiences to Predict Densities and Distribution of Outdoor-Biting Mosquitoes in Rural Tanzania.

Lack of reliable techniques for large-scale monitoring of disease-transmitting mosquitoes is a major public health challenge, especially where advanced geo-information systems are not regularly applicable. We tested an innovative crowd-sourcing approach, which relies simply on knowledge and experiences of residents to rapidly predict areas where disease-transmitting mosquitoes are most abundant. Guided by community-based resource persons, we mapped boundaries and major physical features in three rural Tanzanian villages. We then selected 60 community members, taught them basic map-reading skills, and offered them gridded maps of their own villages (grid size: 200m×200m) so they could identify locations where they believed mosquitoes were most abundant, by ranking the grids from one (highest density) to five (lowest density). The ranks were interpolated in ArcGIS-10 (ESRI-USA) using inverse distance weighting (IDW) method, and re-classified to depict areas people believed had high, medium and low mosquito densities. Finally, we used odor-baited mosquito traps to compare and verify actual outdoor mosquito densities in the same areas. We repeated this process for 12 months, each time with a different group of 60 residents. All entomological surveys depicted similar geographical stratification of mosquito densities in areas classified by community members as having high, medium and low vector abundance. These similarities were observed when all mosquito species were combined, and also when only malaria vectors were considered. Of the 12,412 mosquitoes caught, 60.9% (7,555) were from areas considered by community members as having high mosquito densities, 28% (3,470) from medium density areas, and 11.2% (1,387) from low density areas. This study provides evidence that we can rely on community knowledge and experiences to identify areas where mosquitoes are most abundant or least abundant, even without entomological surveys. This crowd-sourcing method could be further refined and validated to improve community-based planning of mosquito control operations at low-cost.

Inter-epidemic acquisition of Rift Valley fever virus in humans in Tanzania.

BACKGROUND: In East Africa, epidemics of Rift Valley fever (RVF) occur in cycles of 5-15 years following unusually high rainfall. RVF transmission during inter-epidemic periods (IEP) generally passes undetected in absence of surveillance in mammalian hosts and vectors. We studied IEP transmission of RVF and evaluated the demographic, behavioural, occupational and spatial determinants of past RVF infection. METHODOLOGY: Between March and August 2012 we collected blood samples, and administered a risk factor questionnaire among 606 inhabitants of 6 villages in the seasonally inundated Kilombero Valley, Tanzania. ELISA tests were used to detect RVFV IgM and IgG antibodies in serum samples. Risk factors were examined by mixed effects logistic regression. FINDINGS: RVF virus IgM antibodies, indicating recent RVFV acquisition, were detected in 16 participants, representing 2.6% overall and in 22.5% of inhibition ELISA positives (n = 71). Four of 16 (25.0%) IgM positives and 11/71 (15.5%) of individuals with inhibition ELISA sero-positivity reported they had had no previous contact with host animals. Sero-positivity on inhibition ELISA was 11.7% (95% CI 9.2-14.5) and risk was elevated with age (odds ratio (OR) 1.03 per year; 95% CI 1.01-1.04), among milkers (OR 2.19; 95% CI 1.23-3.91), and individuals eating raw meat (OR 4.17; 95% CI 1.18-14.66). Households keeping livestock had a higher probability of having members with evidence of past infection (OR = 3.04, 95% CI = 1.42-6.48) than those that do not keep livestock. CONCLUSION: There is inter-epidemic acquisition of RVFV in Kilombero Valley inhabitants. In the wake of declining malaria incidence, these findings underscore the need for clinicians to consider RVF in the differential diagnosis for febrile illnesses. Several types of direct contact with livestock are important risk factors for past infection with RVFV in this study's population. However, at least part of RVFV transmission appears to have occurred through bites of infected mosquitoes.