Although febrile illnesses are the most common reasons for seeking medical care globally, ^{1 , 2} diagnosis and management of these illnesses are challenging due to their diverse causes and the general nature of their symptoms, which are hard to distinguish clinically. ^{3 , 4} In malaria-endemic settings, most febrile cases are often considered to be malaria, due to the similarity of their clinical presentation, leading to under-reporting and mismanagement of other causes of fevers. ^{5 , 6} However, recent advancements in diagnostic technologies, along with intensified control efforts, have shed new light on the broader landscape of febrile illnesses, revealing a complex interplay of pathogens contributing to fevers in endemic areas. ⁷ The widespread use of malaria rapid diagnostic tests (RDTs) has been pivotal in this shift. These tests swiftly and rapidly confirm malaria infections by detecting parasite proteins, aiding healthcare providers in making confirmatory diagnoses and distinguishing malaria from non-malarial fevers. ⁸ In practice, there are limited point-of-care (POC) tests for other pathogens that cause non-malaria fevers ⁹ and thus, the causes of other pathogens responsible for fevers apart from malaria are not routinely detected. This leads to poor management of cases without malaria, as well as a missed opportunity to capture other fever-causing pathogens. ¹⁰ With the recent decline of the malaria burden in areas that were hyper-endemic for many years, failure to detect the different causes of fevers in patients with negative RDT results is an emerging dilemma for service providers. Thus, urgent actions are required to develop POC tests for multiple pathogens and algorithms for their effective management.

In recent years, Tanzania, like many other endemic countries, has witnessed a remarkable decline in malaria transmission and disease burden in different areas. ¹¹ However, the decline in malaria cases does not correspond to the decrease in febrile patients in areas of different malaria endemicity. In some locations, the proportion of patients with fever but without malaria parasites has remained unchanged or increased significantly. ¹² This discrepancy highlights the increasing recognition that many febrile illnesses previously treated presumptively as malaria are actually of non-malarial origin. This is especially noticeable in areas with low malaria transmission, where a large proportion of individuals with fever test negative for malaria upon visiting health facilities. Conversely, in high transmission settings, a positive RDT result does not always indicate that malaria is the only cause of fever, ^{13 , 14} because individuals may have developed naturally acquired immunity to malaria, ^{15 , 16} and the presenting symptoms may result from co-infections with different pathogens. Therefore, a comprehensive, evidence-based strategy with a clear management algorithm is urgently needed for fevers not caused by or occurring concurrently with malaria infections.

While it is challenging to determine whether there is an increase in NMFIs, more work should be done to enhance our understanding of the epidemiology of these conditions and pathogens causing NMFIs. Recent reviews revealed that NMFIs are widespread in Africa, and most of them are dominated by bacterial and viral aetiologies. ^{17 – 19} A recent study in Nigeria found that 37.0% of febrile cases were not caused by malaria. Among these cases, 54.7% were due to viral infections, while bacterial infections caused 32.1% of the infections. ²⁰ Similarly, a study in Senegal identified other causes of fever in 23.0% of febrile cases. ⁷ In another study conducted in Guinea-Bissau, respiratory viruses were the most common pathogens, detected in 58.9% of non-malarial febrile cases, followed by bacteria, which were found in 22.6% of the cases. ²¹

In contrast to malaria, other causes of febrile illnesses are frequently unnoticed in many regions of Sub-Saharan Africa due to the lack of comprehensive guidelines for managing febrile cases when malaria is not the cause. ^{6 , 22} This neglect stems from limited human and financial resources, ²³ and a lack of understanding and insufficient appreciation of the public health burden posed by NMFIs. ²⁴ The limited awareness is further compounded by inadequate training and diagnostic capacity, which hinders the ability of healthcare workers to correctly identify and appropriately manage NMFIs. ^{25 – 27} In many regions, diagnostic tools for these illnesses are either unavailable or underutilised due to logistical challenges, leading to presumptive treatment. As a result, authorities are compelled to prioritise diseases deemed more threatening to public health, while NMFIs are overlooked due to insufficient evidence of their true burden. ²⁸ Subsequently, the lack of evidence-based information on the burden of these illnesses further complicates the situation, leading to disregard for the potential threat of NMFIs. ²⁹ This cycle of neglect continues as limited data on NMFIs hampers the development of effective policies and guidelines, and diminishing incentives to invest in diagnostic capacity. In addition, the decline of malaria is found to be associated with an increase in antibiotic prescriptions, ^{30 , 31} highlighting the potential presumptive treatment of NMFI cases with antibiotics, which is inappropriate and could result in antibiotic resistance, a growing global concern. ^{32 , 33}

Healthcare workers in Tanzania, as elsewhere, face challenges in managing febrile patients with negative malaria RDTs. This highlights the urgent need to better understand the epidemiology and burden of non-malarial febrile illnesses. Although previous studies conducted in Tanzania focused on identifying aetiological agents of NMFIs at selected sites, the extent of the burden and distribution patterns of NMFIs remain poorly understood. This study utilised the largest data set generated by the ongoing project on molecular surveillance of malaria in Mainland Tanzania (MSMT), ^{34 – 36} and aimed to map the country-wide prevalence and distribution patterns of NMFIs across various regions located in different malaria transmission strata. The findings from this study will inform future research and healthcare planning, and potentially improve the diagnosis and management of febrile illnesses beyond malaria, in areas of varying endemicity in the context of the ongoing epidemiological transition of malaria transmission intensities.

This was the first health facility-based cross-sectional study involving symptomatic patients suspected of having uncomplicated malaria, conducted by the MSMT project, covering all 26 regions of Mainland Tanzania. Unlike community surveys, which are routinely implemented in school children, ³⁹ or under-fives. ^{11 , 40 – 42} It provides the largest scan of malaria in HF settings across the entire country. The data have also been utilised to assess the prevalence and patterns of NMFIs in Tanzania and provide useful information for guiding policy and decisions for controlling different pathogens associated with NMFIs. The study found that more than 40.0% of febrile patients had NMFIs, and there was a high prevalence of NMFIs with spatial heterogeneity across different regions, characterized by varying malaria transmission intensities in Mainland Tanzania. Occurrence and the odds of NMFIs were higher in females than in males, and in adults compared to younger age groups. School children had the lowest prevalence and, correspondingly, the lowest odds of getting NMFIs. NMFIs varied inversely to malaria transmission intensities, with the lowest prevalence in the regions located in the stratum with high transmission intensities and the highest prevalence in the stratum with very low transmission intensities of malaria. The findings provide country-wide scans of NMFIs with varying prevalence, which suggest that more studies are urgently needed to characterise the burden of NMFIs further and develop POC tests and guidelines/recommendations for managing these illnesses alongside malaria.

The findings showed that the prevalence of NMFIs in the different regions of Mainland Tanzania increased with decreasing malaria transmission intensities. This may or may not represent a direct association between the occurrence of NMFIs and the transmission intensity of malaria. In areas with high malaria transmission, the rate of individuals harbouring malaria parasites is high compared to areas with low transmission. However, most of the people in high transmission tend to have high acquired immunity due to high rates of exposure to infective bites by mosquitoes. ⁴⁶ Thus, in high-transmission areas, not all malaria infections cause symptoms, as some individuals may remain asymptomatic even when they have high parasitaemia. ⁴⁷ When such individuals develop symptoms, they will test positive for malaria, while malaria may potentially not be the direct cause of the symptoms. ¹³ As a result, any individual who tests positive for malaria by RDT will be considered not to have NMFIs (based on the criteria used in this study), resulting in a low prevalence of NMFIs and potentially improper case management of infections with fever as the main symptom. On the contrary, in areas with low malaria burden, most of the febrile patients will test negative for malaria, thus reducing the masking effect of malaria infections and resulting in high NMFI prevalence. Therefore, while it may be true that in some areas where the prevalence of NMFIs is high and the burden of malaria is low, co-infections with malaria, which is common in areas of high transmission intensities, may introduce bias and act as a confounder. Thus, other causes of fever should always be investigated even in malaria-positive individuals, particularly in high malaria-burden regions, although this may be challenging under current clinical conditions with limited POC tests for other pathogens. ¹³

This study showed high variations in NMFI prevalence among patients in different age groups, with adults exhibiting a higher prevalence than under-fives and school children. The increased prevalence in adults suggests that the adult population may be more exposed to febrile illnesses due to increased mobility, occupational exposure, and sometimes immunosenescence. Taking more responsibility, adults may be exposed to multiple and higher doses of infectious agents than younger children. Increased exposure frequently raises the chance of contracting an infection, but there is no apparent evidence linking this risk to the findings of this study. ⁴⁸ The observed higher prevalence in under-fives could be due to the vulnerability of this group to infections. These findings are similar to those reported in Malawi, where 72.0% of under-fives and 77.0% of adults had NMFIs. ²⁹ The low prevalence of NMFIs among school children could be attributed to the high prevalence of malaria in this group, as previously reported by other studies, ^{44 , 49 , 50} since febrile patients were excluded from NMFI analysis if they tested positive for malaria by RDT. Additionally, the low prevalence of NMFI among school children could be attributed to their relatively stronger immunity acquired through repeated antigenic exposure. It may also be because, at the age of 5-15, the immune system is just starting to mature. As a result, most infections can be prevented by the immune system, making this group less susceptible to most NMFI-causing pathogens. ^{51 , 52} This is consistent with previous research conducted elsewhere, where school children had the lowest prevalence of NMFI compared to under-fives and adults. ^{29 , 53} The pattern observed in this study is similar to what was reported by other studies on malaria-related fevers, which showed a higher prevalence of malaria in school children, making them have NMFIs in the absence of tests for other pathogens. ^{44 , 49} This results in a low prevalence of non-malarial fevers since a large proportion of the fevers are parasitologically attributed to malaria, even if there is no evidence of clinical association unless multiple tests are done to rule out any other infections by fever-causing pathogens.

The slightly higher NMFI prevalence observed in females compared to males may be attributed to various social, biological, and healthcare-seeking behaviors. In many settings, women are more likely to seek healthcare services, leading to higher detection rates of febrile illnesses. Additionally, biological differences such as immune response variations between sexes may also contribute to this observation. ^{54 , 55} Due to social and biological factors, the prevalence of malaria is usually higher in males compared to females, ^{44 , 49 , 50} which results in the exclusion of more males than females in the NMFI analysis, since the potential for malaria co-infection with other febrile aetiologies was not pursued in this study. However, further research is needed to fully understand the underlying causes of this disparity. The findings of higher odds of NMFIs are consistent with what was reported by other studies, which showed a higher prevalence of NMFIs in females (70.0%) compared to males (68.0%). ²⁹

The key strength of the study is its extensive coverage, utilising a large number of samples from all 26 regions of Mainland Tanzania, thus providing a comprehensive representation of the country’s diverse population and transmission settings. However, this study had some limitations. As a cross-sectional study, the data may not accurately represent the actual prevalence of NMFIs in a given area, as the study only captured a single time point and, therefore, had a limited temporal scope. Also, the data for this study were collected as part of the MSMT project, whose sites were purposively selected to maximise the recruitment of patients with malaria based on the detection of RDT-positive results. Therefore, the sites may be biased towards high transmission areas, even in low transmission regions, given the current heterogeneous nature of malaria in Mainland Tanzania. ^{56 , 57} This selection criterion, while operationally necessary to meet recruitment targets, may have underestimated the proportion of NMFIs, particularly in low-transmission settings. Thus, future studies should consider inclusive sampling covering areas of different levels of malaria burden, preferably using DHIS2 data for a more comprehensive mapping of NMFIs country-wide. Additionally, this study could not explore the specific causes of NMFIs because it was not designed to offer POC or laboratory tests for other pathogens. However, it has highlighted the magnitude of this problem in the entire country, with a higher burden of NMFIs, particularly in areas of low transmission intensities, as previously reported by other studies. ¹³ Analysis to address this issue will need to be performed and reported in future studies to appropriately inform policy and decisions for targeting and better case management, and the control of NMFIs.

Non-malarial febrile illnesses were fairly common, and their burden and distribution patterns varied significantly across regions and malaria transmission strata. Females, adults, and individuals from areas with low and very low transmission intensities of malaria had a higher prevalence of NMFIs and an increased likelihood of experiencing non-malarial fevers compared to males, under-fives, school children, and individuals living in settings with high malaria transmission intensities. These findings have important implications for healthcare planning, offering critical insights to enhance the diagnosis and management of febrile illnesses beyond malaria. The results further suggest that the identified groups of patients should be appropriately targeted with POC tests and treatment strategies. By country-wide mapping of NMFIs, this research contributes to a better understanding of the local epidemiology of NMFIs and supports the development of more effective management and control strategies. Addressing the gaps in evidence-based information on NMFIs will ultimately lead to improved patient outcomes and better healthcare delivery in regions with varying endemicity of malaria and other fever-causing pathogens.

This large health facility survey was part of the MSMT project, whose protocol was reviewed and approved by the Medical Research Coordinating Committee (MRCC) of the National Institute for Medical Research (NIMR), on 15 November 2022, with certificate number NIMR/HR/R.8c/Vol. I/2193. Permission to conduct the study in the different regions was sought from the President’s Office, Regional Administration and Local Government (PO-RALG). Before participating in the survey, all participants were asked and provided individual consent (or assent for children aged 7–17 years of age) for their participation in the survey. For children under the legal age of adulthood in Tanzania (<18 years), consent was obtained from a parent or guardian. An informed consent form was developed in English and translated into Kiswahili and used to obtain consent both verbally and in writing from all participants. All participants agreed and signed the consent or assent form or provided a thumbprint in conjunction with the signature of an independent witness in case the study participant was illiterate.

The previous version of this manuscript was published as a preprint ⁵⁸ and original pre-preprint underwent rapid review.

Supplementary Table 1.

Regions				Sex						Age group
				Female			Male			<5 years			5 -< 15 years			≤15 years
	Tested for malaria	Negative malaria tests	Proportion of NMFI (%)	Tested for malaria	Negative malaria tests	Proportion of NMFI (%)	Tested for malaria	Negative malaria tests	Proportion of NMFI (%)	Tested for malaria	Negative malaria tests	Proportion of NMFI (%)	Tested for malaria	Negative malaria tests	Proportion of NMFI (%)	Tested for malaria	Negative malaria tests	Proportion of NMFI (%)
Arusha	561	263	46.9	302	166	55.0	259	97	37.5	198	105	53.0	94	27	28.7	269	131	48.7
Dar es Salaam	1117	792	70.9	559	412	73.7	558	380	68.1	340	286	84.1	161	108	67.1	616	398	64.6
Dodoma	841	514	61.1	482	312	64.7	359	202	56.3	320	209	65.3	138	77	55.8	383	228	59.5
Geita	461	131	28.4	261	82	31.4	200	49	24.5	245	82	33.5	95	13	13.7	121	36	29.8
Iringa	95	58	61.1	47	27	57.4	48	31	64.6	44	31	70.5	26	10	38.5	25	17	68.0
Kagera	2352	965	41.0	1360	541	39.8	992	424	42.7	1333	549	41.2	328	130	39.6	691	286	41.4
Katavi	578	248	42.9	377	159	42.2	201	89	44.3	201	103	51.2	107	38	35.5	270	107	39.6
Kigoma	460	112	24.3	261	73	28.0	199	39	19.6	240	50	20.8	60	9	15.0	160	53	33.1
Kilimanjaro	2154	1844	85.6	1272	1135	89.2	882	709	80.4	308	281	91.2	238	193	81.1	1608	1370	85.2
Lindi	426	96	22.5	251	62	24.7	175	34	19.4	269	59	21.9	49	6	12.2	108	31	28.7
Manyara	596	261	43.8	335	153	45.7	261	108	41.4	165	88	53.3	113	43	38.1	318	130	40.9
Mara	907	279	30.8	525	153	29.1	382	126	33.0	246	106	43.1	270	66	24.4	391	107	27.4
Mbeya	560	243	43.4	332	144	43.4	228	99	43.4	208	95	45.7	82	30	36.6	270	118	43.7
Morogoro	476	146	30.7	315	107	34.0	161	39	24.2	184	47	25.5	98	21	21.4	194	78	40.2
Mtwara	820	196	23.9	472	116	24.6	348	80	23.0	522	119	22.8	78	13	16.7	220	64	29.1
Mwanza	455	113	24.8	251	69	27.5	204	44	21.6	222	64	28.8	106	12	11.3	127	37	29.1
Njombe	402	62	15.4	225	42	18.7	177	20	11.3	102	14	13.7	104	16	15.4	196	32	16.3
Pwani	667	332	49.8	380	193	50.8	287	139	48.4	315	163	51.7	121	42	34.7	231	127	55.0
Rukwa	662	274	41.4	397	166	41.8	265	108	40.8	267	117	43.8	150	46	30.7	245	111	45.3
Ruvuma	526	194	36.9	280	113	40.4	246	81	32.9	245	93	38.0	122	32	26.2	159	69	43.4
Shinyanga	430	84	19.5	250	49	19.6	180	35	19.4	219	54	24.7	97	8	8.2	114	22	19.3
Simiyu	477	140	29.4	306	102	33.3	171	38	22.2	250	95	38.0	74	5	6.8	153	40	26.1
Singida	524	179	34.2	298	108	36.2	226	71	31.4	341	118	34.6	51	14	27.5	132	47	35.6
Songwe	464	147	31.7	269	87	32.3	195	60	30.8	156	51	32.7	118	28	23.7	190	68	35.8
Tabora	1004	393	39.1	569	216	38.0	435	177	40.7	605	253	41.8	101	35	34.7	298	105	35.2
Tanga	553	207	37.4	348	126	36.2	205	81	39.5	139	44	31.7	141	48	34.0	273	115	42.1
Total	18568	8273	44.6	10724	4913	45.8	7844	3360	42.8	7684	3276	42.6	3122	1070	34.3	7762	3927	50.6

The data supporting this study are available upon reasonable request from the corresponding author (MDS), subject to institutional approval by the Medical Research Coordinating Committee (MRCC) of the National Institute for Medical Research (NIMR), and a signed data transfer agreement. Data cannot be publicly shared due to ethical considerations. Access will be granted in accordance with the MRCC approval.