In the present study there was a significant reduction in data incompleteness; with missing variables between 2012 and 2019. Specifically, the number of clinical suspects with missing data variables declined between 2012 and 2019 by approximately 4-fold and confirmed cases with about 7-fold. Decreasing trend in data incompleteness overtime, is plausible indication of huge improvement in data quality which thereby an implication for improving programmatic performance over the years.
There was an overall notable difference in both total number of clinical suspects (3758) and confirmed malaria cases (467) recorded at HCs (source data) and HOs (HMIS data). For the 8-years period, discrepancies in clinically suspected and confirmed cases were observed between the HOs compared to the HCs. During 2012 and 2018 the numbers of clinical suspects recorded at HCs were consistent with HO data. In these years the numbers of confirmed cases were higher at HO records than HC records. Yirgacheffe rural district had the highest deviation in terms of confirmed malaria records between HC and HO data followed by Dilla town and Dilla zuria district, whereas Wonago district was the least. Similar to our finding, a three-month facility-based study comprising of various settings conducted in southern Ethiopia showed that majority of facilities under-reported total malaria (both confirmed and clinical malaria) cases . This in malaria data between the two systems, HC and HO, could be due to errors during entering the data from the sources (HCs) into recording formats of HMIS, lack of cross-checking and proofing habits, training gaps on HMIS data use and unintentional/intentional false reports. In addition, limited computer access and skill, inadequate technical support , poor data management skills and limited functionality of electronic data management systems  might be the likely reasons for HMIS implementation challenges.
Concerning the diagnostic performance, the proportions of clinically suspected cases against confirmed cases were increased from 6.91 in 2012 to 16.32 in 2019. The highest proportion was recorded in 2019, whilst the lowest was during 2013. This revealed that the 'non-malarial' febrile cases were increasing from 2012 to 2019, which can be an indication of declining lab capacity of detecting malaria parasites. This declining lab capacity of detecting malaria might be due to the fact that the increased false negative reports associated with reduced sensitivity of microscopy with decreasing parasite densities , unable to detect sequestered P. falciparum parasites  and low competency of microscopists . In the other way, such increased number of non-malarial febrile illnesses might be related to other febrile cases including yellow fever virus [17, 18] and typhoid fever  infections, as per the studies conducted in southern Ethiopia. In addition, this high number of non-malarial febrile illness might be due to fevers among positive individuals with malaria where the fever is coexisted with but not caused by the Plasmodia infection . If laboratory performance percent confirmed declines it means; laboratory performance was decreasing over the years or something causing febrile illness in the area is increasing. Misdiagnosis and incorrect treatment of such non-malarial febrile illnesses with antimalarial drugs is possibly to contribute to rapid emergence of antimalarial drug resistance [21, 22] in the study area.
There was an overall reduction of malaria case from 2012 to 2019. According to data from HCs (source data), a maximum of 16,037 and a minimum of 2,546 of cases were observed during 2013 and 2018, respectively with 8.34 percent reduction. 2013 and 2016 were the exceptions to the declining trend as there were small epidemics in these periods in some parts of the Zone. Over the eight years period, overall, there was malaria positivity rate of 11.79%, data from the HCs. This positivity rate was comparable with certain studies done in Ethiopia including from Batu town (12.43%) , Arsi Negelle (11.40%)  and Halaba special district (9.47%) . In contrast, higher overall malaria positivity rates were reported from related studies conducted in south-central Ethiopia , southern Ethiopia  and abroad in Dakar, Senegal  with 33.83%, 21.79% and 19.68% respectively. On the other hand, the present figure was higher than records in other local studies [29, 30]. These differences might be due to the variation in quality of laboratory diagnoses, difference in intervention measures, micro-climatic/altitudinal differences, and presence of constructions responsible for occurrence of temporary and permanent dams and drug and insecticide resistances. The possible contributing factors for the peaks/epidemics of malaria cases in 2013 and 2016 could be associated with feeble intervention activities in certain areas of the Zone.
- falciparum and P. vivax were detected where equivalent; congruent results were reported in some other parts of Ethiopia [26, 27]. While other local studies [23, 25, 31] documented that the dominant species was P. vivax. The proportion of mixed infection in this study was congruent with other studies [26, 30], whereas inconsistent with other reports [27, 31]. The likely reason for the slightly higher proportion of P. falciparum over P. vivax could be related to temperature; that is temperatures more than 18°C for P. falciparum and more than 15°C for P. vivax is suitable for the growth of these two species in human host and mosquito vectors [32, 33]. Apparently, in the current study area the average mean temperature during the eight years period found to be above 18°C. The higher proportion of P. vivax against the national figures could also be an implication for the ability of repeated relapse cases and early emergence of gametocytes during blood-stage infection. In addition, there could be heterogeneity of the Duffy phenotype and the high number of vulnerable Duffy-positive individuals that associated with population movement  in the study area. Environmental fluctuations that change target mosquito species abundance might have an impact on Plasmodia species occurrence . The issue demands additional study. The possible reason for scarcity of mixed infections in this co-endemic area might be a competitive or an antagonistic effect of one Plasmodium species over the other within the human host during co-infection [26, 35].
Males were slightly more infected (51.51%) by malaria than females (48.49%) over the eight-year period. This was paralleled with other studies conducted in different parts of Ethiopia [23, 26, 27, 31]. However, this finding was not consistent with other reports in southern Ethiopia  and elsewhere in Mozambique  where higher malaria cases in females were documented. Individuals in the age group of 15 and above were also more significantly affected. This was in line with other local studies [23, 31]. Inconsistent result was observed in southern Ethiopia  arguing that malaria cases cluster among the under-5. And a finding in Metema, northwest Ethiopia by Ferede et al.  showed that 5-14 years old were more infected. Possible justifications for the higher occurrence of malaria among males and older age group could be their engagement in various outdoor activities and staying outdoors during the nights . Apart from outdoor exposures, differences in treatment-seeking behavior, access to health facilities and travel history  might be the possible contributors for the sex- and age-based variations of malaria cases. In addition, a review report revealed that adult females are better protected from parasitic diseases than males due to genetic and biological (hormonal) factors .
The peak number of confirmed malaria cases was recorded during autumn followed by spring, summer and winter with a statistically significant variation. This seasonal peak in malaria cases in autumn deviates from various studies in Ethiopia which is during spring after the main rain season [24, 26, 27, 31]. In addition, nationally the main malaria transmission season is from September to December following the peak rain season [1, 4]. This trade-off in seasonal peak of malaria cases might be as a result of varying climatological conditions (rainfall pattern and temperature changes) in the area against other settings. Despite the high prevalence of malaria cases during the three seasons, there were a substantial number of confirmed malaria cases in the dry (winter) season in this study. These, absence of significant variation in the proportion of the P. vivax and P. falciparum burden and almost, year-round presence of malaria might suggest the presence of suitable local environments for mosquitoes. The comparable proportion of P. vivax against P. falciparum in winter might be explained by the fact that P. vivax has ability to relapse rather than new infections. Since such traits could affect the temporal patterns of P. vivax infections.
Overall, high number of clinical suspects and confirmed malaria cases were documented in Dilla town (urban) and Dilla zuria district (sub-urban) as compared to other districts. Except in 2013 and 2019, Dilla town annual malaria cases remained the highest all over the 8-year period. The highest confirmed cases during these two years were overtaken by Kochore in 2013 and Dilla zuria districts in 2019. While the lowest was from Yirgacheffe rural district. In general, though an overall declining trend of confirmed malaria cases from 2012 to 2019, peaks were recorded in Kochore during 2013 and Dilla town in 2016. Although there is expectation of a better documentation, treatment-seeking behavior, access to health facilities, community knowledge and coverage of intervention activities in urban settings, the current data pointed to the contrary. Thus, in this study, high burden of urban and suburban malaria was noted. This could be because of massive construction activities (like road, house and small dams) and presence of coffee processing sites in Dilla town and its vicinity that could create suitable habitat for mosquito breeding. Travel history , differences in the competence and skills of the laboratory personnel and relatively good reporting system might also be the main responsible factors influencing the prevalence of malaria in Dilla town compared to rural districts. There have been healthy ongoing malaria control activities incorporating environmental management, indoor residual spraying (IRS), long-lasting insecticide-treated nets (LLINs) and artemisinin-based combination therapy in the area. These intervention activities could be attributed for the decreasing trends of malaria in other sites of the Zone. In addition, micro-environmental variations, micro-climatic situations  and changes in intervention (like IRS and LLINs) periods might have effect for these spatial differences of malaria cases.
Monthly rainfall and minimum temperature demonstrated statistically significant positive correlation with malaria cases. Previous studies in Ethiopia [41, 42] and elsewhere  documented similar findings. However, the result of the current study on the association of rainfall and malaria cases was deviating from previous findings, stating higher rainfall does not necessarily influence the malaria changes [45, 46]. In contrast to our finding, minimum temperature was weakly correlated with malaria cases in southeast Ethiopia . Ideally, rainfall and minimum temperature play a vital role in breeding and survival of malaria vectors and the respective parasites. Moreover, average monthly maximum temperature and relative humidity were weakly correlated with malaria cases. In disagreement to our finding, studies conducted in Jimma, Ethiopia by Alemu and others  and Sena and colleagues  in Gilgel-Gibe, southwest Ethiopia reported that inter-monthly relative humidity was significantly associated with monthly malaria cases.
The limitation of this study was incompleteness of patient data in the register with missed variables and only 8-year data were available during the data collection time at the HCs. Missing of asymptomatic cases and poor competence of the laboratory personnel at HCs could be the other limitations. Furthermore, clinically treated patients’ (without laboratory confirmation) data and malaria mortality data were not recorded in the laboratory registration logbooks. Hence, interpretation of the finding should be with caution.